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I am inspired by this paper (see the excert below)
REVIEW
published: 31 October 2019
doi: 10.3389/fnhum.2019.00378
Edited by:
Felix Blankenburg,
Freie Universität Berlin, Germany
Reviewed by:
Timothy Joseph Lane,
Taipei Medical University, Taiwan
Jakub Limanowski,
University College London,
United Kingdom
*Correspondence:
Tam Hunt
Specialty section:
This article was submitted to
Cognitive Neuroscience,
a section of the journal
Frontiers in Human Neuroscience
Received: 08 January 2019
Accepted: 07 October 2019
Published: 31 October 2019
Citation:
Hunt T and Schooler JW (2019)
The Easy Part of the Hard Problem:
A Resonance Theory
of Consciousness.
Front. Hum. Neurosci. 13:378.
doi: 10.3389/fnhum.2019.00378
The Easy Part of the Hard Problem: A
Resonance Theory of Consciousness
Tam Hunt* and Jonathan W. Schoole
Dehaene (2014) states the problem clearly (p. 211): “[C]ould any brain image ever prove or disprove the existence of a mind?” He answers this question in the affirmative, with various discussions about the neural correlates of consciousness and “signatures of consciousness” (what he considers to be the necessary and sufficient correlates of consciousness), but also recognizes that (p. 214) “no single test will ever prove, once and for all, whether consciousness is present.” He instead recommends a battery of tests be developed to give more confidence about the presence of consciousness in various contexts, focused on human subjects.
Testing the framework presented here should focus initially on the three conjectures in our Table 1. This approach follows the Lakatosian research program (Lakatos, 1968) that focuses on testing the “hard core” principles of any given theory. Conjectures 1–3 in Table 1 are the core of General Resonance Theory. There are many ways that various MCC may be measured to test conjectures 1–3 and we are fleshing out these ideas in other work.
Here again are the three primary conjectures of General Resonance Theory:
Conjecture 1: Shared resonance is what leads to the combination of micro-conscious entities into macro-conscious entities (“the shared resonance conjecture”).
Conjecture 2: The boundaries of a macro-conscious entity depend on the velocity and frequency of the resonance chains connecting its constituents (“the boundary conjecture”).
Conjecture 3: Any biological macro-conscious entity will have various levels of subsidiary/nested micro- and macro-conscious entities (“the nested consciousness conjecture”).
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Consciousness is emarging propert of metter/energy yes ?
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I'm a college student and now I'm doing research in medical imaging. I need normal image dataset for my research. Where can I get normal CT/MRI brain image dataset? I really need this dataset for data training and testing in my research. Your help will be helpful for my research. Thank a lot:).
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There are several sources where you can access normal CT brain image datasets for research or academic purposes. Here are a few options:
  1. Open Access Medical Image Repositories:The Cancer Imaging Archive (TCIA): TCIA (https://www.cancerimagingarchive.net/) provides a vast collection of publicly available medical imaging datasets, including CT scans. While it focuses on cancer-related imaging, it also includes normal cases that can be used for reference or comparison. Open Access Series of Imaging Studies (OASIS): OASIS (https://www.oasis-brains.org/) offers a collection of MRI brain scans, including normal cases. Although it specifically focuses on MRI, it may still be a valuable resource for brain imaging research. Medical Imaging Databank (MIDB): MIDB (https://medpix.nlm.nih.gov/home) is a resource from the National Library of Medicine that offers a collection of radiological images, including CT scans. It provides access to both normal and pathological cases.
  2. Research Institutions and Databases:Local Research Institutions: Contact local research institutions or academic medical centers that may have CT brain image datasets available for research purposes. They may have their own collections or collaborations with other organizations. Radiology Departments: Reach out to radiology departments in hospitals or medical facilities to inquire if they have anonymized CT brain image datasets available for research or educational use. Some institutions may be willing to share datasets with proper agreements and adherence to privacy regulations.
  3. Academic Publications and Data Supplements:Check academic publications related to brain imaging research. Some studies provide access to their datasets as supplementary materials. Explore journals or conference proceedings in the field of radiology, neuroimaging, or medical imaging.
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I have been trying to analyse neurons for spine density and size using ImageJ.The images are from fixed brain section taken using confocal microscope. but the background fluorescence is interfering with the analysis as the software is unable to distinguish between actual spine and background noise. What plugins/macros can be used to reduce noise and clearly outline the structure of the neuron. Please do not hesitate to ask for more details in case you think you could help me out ! Please find the iimage attached. Many Thanks, - Raj
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Try to use ImageJ, select "Process" > "Subtract Background" > "Light Background" + "Separate Colors" > Save the image. Hope it helps.
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Brain Tumor Imaging Protocol will reduce variability and increase accuracy in determining progression and response of investigational therapies.
In the pictures below, with the FFT and DFT methods and the PCA phase recovery, which is common in optical microscopes, I obtained the magnetic resonance imaging (MRI) phase of the human brain tumor and the phase obtained.
Can the process be performed on MRI without prescribing Jumpstarting Drugs (JBTDDC)?
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سلام عقیل عزیز
ایمیل بنده در قسمت نام کاربری موجود است
آرزوی موفقیت
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I am working on a project where I am able to perform conversion of NIFTI to JNIFTI file. These are neuroimaging files that require conversion so that I could integrate this into NiBabel, which is a package that gives access to some common medical and neuroimaging file formats. How can I perform this conversion in Python?
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I don't know how to program with Python, and I haven't converted these files either. But I think that by using the link below and MATLAB software, you can open your files and probably convert them to other formats.
Best regards
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Dear experts,
I am new to fMRI and I am working with rat fMRI data. I am performing the preprocessing steps in fsl (FMRIB Software Library) and since it designed for human brain, I must scale up the voxel size of rat brain image by 10.
I know that I probably must work with scl_slope and scl_inter in nifti header and I use fsledithd command to change the scl_slope to 10 (Now it is set to 1). but when I change the scl_slope in nifti header, the image doesn't change ( the voxel size remains unchanged.) and I think I must use fslcreatehd command to make these change to my image but I don't know how to do that. if this procedure is right please tell me how I must do that.
Also, I edit the voxel size directly with fsledithd(edit pixdim1, pixdim2 and pixdim3 instead of scl_slope and scl_inter) and it seems that it works, but, I don't know that it is correct to edit those parameter instead of scl_slope or not.
Thank you.
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Thank you for your responses,
I found that in FSL we can change niftii header info by using of fsledithd command, and then change the dx, dy, and dz parameters (x10) as well as sto_xyz_matrix.
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1. Science folks unanimously agree about a fixed definition for “Theory of Mind” or "Mentalizing"! That I think is a philosophical paradox as theory of mind has this very pivotal cannon of being open in empathizing and understanding different beliefs through attribution of mental state as in beliefs, intentions, knowledge and emotion. Thus, how could we all agree to establish one definition for “Theory of Mind” which conveys elimination of all other definitions or disregard openness to other definitions of “Theory of Mind” itself that might be quite different from the typical definition of theory of mind. As if one might staunchly emphasize that they believe in animal advocacy and rights but still keeps a songbird in a cage! I believe that some definitions cannot be strictly defined as a single omnipresent definition and depending on the subject and application would vary in definition. Theory of Mind can have one definition in mentally healthy human and yet another but not incorrect definition in mentally disordered people. Not to mention that theory of mind has been reported to be a personality trait in non-human primates as well!
Do you agree... or disagree?
2. There are neuropsychological assessments through sessions or interviews... But what about an efficient or statistically reliable "experimental" method of assessment for theory of mind in humans and non-human primates?! Theory of mind is a rather complex behavior which not only includes one's own beliefs or intents but also deciphers those of the others.
We have used "eyes task", etc. during neuroimaging to evaluate theory of mind. Scientists using such simple tasks and fMRI with all its limitations in terms of noise, resolution and processing to test mentalizing. Results are amazing but couldn't we develop better tasks and less limited modalities to assess a behavior with such complexity that involves numerous brain regions at once?
Maybe?...
3. This is a social trait! When someone fails to develop mentalizing (either due to neurological disorders such as schizophrenia, autism... or due to still unknown mechanisms of acquired behaviors and social environment) which can be represented as a wide spectrum of complex behaviors from misunderstanding/incomprehension of beliefs or intentions which are different, unempathetic adamancy to disrespecting or denigrating and disparaging others' beliefs; wouldn't it be quite tricky to merely observe and assess underlying brain functions in a singled out subject via current imaging or experimental modalities?
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No veo la explicación científica de este concepto
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I have been trying to find studies of adults who experienced adverse childhood events/childhood trauma that assess the link between ACEs and outcomes (bipolar disorder, PTSD/cPTSD, etc) using multiple measures to determine cause and effect.
A hypothetical example would be a study that assesses whether childhood emotional abuse/neglect (ACE) is associated with any 5-HTTLPR polymorphism (genetics), SLC6A4 hypermethylation (epigenetics), AND amygdala activity (fxn) in people with bipolar disorder (negative outcome) but not healthy controls who experienced similar severity of childhood emotional abuse/neglect
I know this is a huge lift and would require a somewhat large study but right now the story is missing a comprehensive view of the molecular and functional changes due to ACEs causes leads to negative outcomes.
Thank you in advance for any help you can give
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I find it quite interesting how experiences with rejection at such a young age can be associated with personality disorder development. Enjoy your research!
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I read a research paper investigating brain electrical waves using EEG. In this paper, the authors stated that participants were ineligible to involve if they had a history of neurological disorders, reported using drugs, or if they were left-handed. I am curious about the correlation between EEG and handedness? Especially, why left-handedness was excluded in this research?
Thank you for any answer
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Did the study examine anything involving language? Nearly all EEG studies assessing any form of language processing include only right-handed individuals since (most) language processes are lateralized to the LH in such individuals.
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I am using brain image database which is .mat format.
I has 3000 images in .mat format.
I want to convert data into .csv format.
Please guide
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Hi,
You may try this
M = dlmread('FileName.mat', '\t', 1, 0);
csvwrite('FileName.csv', M)
I attach you a link which may be a better help
Thanks
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I need a CT images database of brain (both normal cases and abnormal cases ) for calculating the midline shift in CT images. 
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brain image data set using CT scans available free of charge?
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The Cancer Imaging Archive:
Have a look, plenty of medical images for various diseases, including normal..
Best Wishes
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hello
I'm a phd student my research is about medical image classification .. i need a dataset and i'm interestiin in brain image ( brain tumor) or if its not available can you provide me a dataset for prostate cancer or lung cancer
thanks
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thank you all for the response
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Dear all, motivated by a variety of MoBI studies currently being conducted in our group, I am thinking of proposing a new Brain Imaging Data Structure (BIDS) extension that addresses MoBI-specific needs for data sharing. This would also encompass flatscreen navigation data or 2D position streams from more conventional studies, so we can easily compare between recordings from different setups. I believe that the community will benefit a lot from clarifying properties specific to recording of spatial data. What are your thoughts on this idea? Is there any ongoing work for BIDS extension for movement data, or would you be interested in creating a new one?
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Hello Martin Knöll , this is an interesting idea. I have not looked into yet which data format / metadata will be useful for processing position data. We are now working on a Google Doc for BIDS specifications for motion data, which currently focuses on motion on smaller scale. Here is the link to Google Doc https://docs.google.com/document/d/1iaaLKgWjK5pcISD1MVxHKexB3PZWfE2aAC5HF_pCZWo/edit?usp=sharing and the thread on GitHub to give you an impression on how the discussion is developing https://bids-specification.readthedocs.io/en/latest/06-extensions.html
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can any one know the MRI brain image database.
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1.Human Connectome Project : https://www.humanconnectome.org/
2.1000 Functional Connectomes Project : http://fcon_1000.projects.nitrc.org/fcpClassic/FcpTable.html
3. Consortium for Reliability and Reproducibility: http://fcon_1000.projects.nitrc.org/indi/CoRR/html/index.html
4. Database for Emotion Analysis using Physiological Signals : http://www.eecs.qmul.ac.uk/mmv/datasets/deap/
5. My Connectome Project : http://myconnectome.org/wp/
7. OpenfMRI : https://openfmri.org/
8. Neuroinformatics database : https://nda.nih.gov/
9. OpenNEURO : https://openneuro.org/
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I've been trying various iba1 antibodies with either Alexa 488 or 647 and am getting a lot of background and have never once seen anything close to resembling a microglia. I've tried blocking with various combinations of 0, .3 or 3.0% milk, 0, .3 or 1.0% BSA, with 4% normal donkey serum and nothing has worked.
Any suggestions would be very much appreciated. Perhaps there are better membrane-bound proteins I could stain for?
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try vector trueview, autofluorescence quenching kit with DAPI (Cat# SP-8500)
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I've recently started pursuing PhD in Medical Image Processing. I am struggling to find a suitable problem to carry out research.
I was initially interested in working on brain images but after doing studies and according to peers' advices lots of works have already done with brain, but still work can be done on:
1. Retinal images
2. Chest radiography
3. Estimating probability of lung cancer etc.
I would be obliged if somebody suggests me some relevant topics(related to brain or other organs) where still there are lots of scopes to work on.
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Well, there are are thousands of interesting topics for many imaging modalities. It might be better to decide what you want to do first, so that you will be able to limit your search.
Do you want to work on image reconstruction, segmentation, analyses or registration? Which imaging modality you want to work with (CT, MRI, ultrasound, mammography, X-rays, SPECT-CT, PET-CT, DEXA, interventional imaging, multimodal, etc)? Are you interested in 2D or 3D imaging, clinical or pre-clinical? Do you want to work with deep learning or no?
After answering some of these questions, look for research groups that are working in a related discipline and their current projects, or recent publications for an inspiration. Also check proceedings of major image processing conferences (e.g., MICCAI, NeurIPS, SPIE Medical Imaging, Fully3D, IEEE MIC)
Good luck!
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Hi there,
I hope you are doing well.
I am working with imaging systems. I am confused about the effects of linear polarizer in such systems ( I mean how a linear polarizer can improve the resolution?) and why working with one polarization is better than two polarization in image processing systems?
Bests,
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Dear William,
Thank you for your response.
Actually the light source that we simulate is a point source light that has spectral width of 50 nm with peak around 400 nm and the detector is photo multiplier tube.
Bests
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Hi there!
I use EEGLAB for processing EEG/ERP data. EEGLAB individually has some functions for topography plot (i.e. pop-topoplot which is popular for Neuroscience researchers). My question is there any additional tools which we could use jointly with EEGLAB to show the brain responses topography in a much better way which we could find in recent publications (i.g. could be a 3D view)? I would appreciate if you could introduce such tools in MATLAB or R.
Cheers,
Reza
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Hi Reza,
I tend to recommend Letswave to my students. It uses parts of EEGLab and Fieldtrip and has a nice interface: https://www.letswave.org/
It also requires less programming experience than some programs making it ideal for performing pre-processing and plotting before you are a MATLAB expert.
Kind regards,
Ben
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Dear Colleagues, I'm currently on my PhD research in Deep Learning for Brain Image Analysis. Kindly help me check the attached Problem Statement and advise if those problem researchable. If they are not, kindly provide with suggestions on current debates, discussions and issues in deep learning. Thank you
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check out Shadi Albarqouni
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i want to use it for semantic automatic annotation 
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kindly provide some datasets with ground truth for Alzhemeirs and normal brain for white and gray matter
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I am working on a project related to neuro-degenerative diseases. Can any one guide me toward a PSP&MSA (MRI) Dataset? I searched over the internet but was unable to find.
OR if any of you have in your drive, is it possible to share that with me?
That can help me a lot.
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For brain MRI Images you may consider this dataset.
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I am working on ultrasound image quality that's why i need some vital link.
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Deleted research item The research item mentioned here has been deleted
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Hi,
Below I am attaching the chapter for your reference.
Thanks
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Hi
Plz suggest from where i can get mri brain image dataset for parkinson disease.
Although i have applied from ppmi, but it will take time.
Thanx
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Stroke is possibly the second most common disease that causes death, apart from disability. With BILLIONS spent on research, etc, one would imagine (and with NINDS getting a large chunk of federal dollars) that a basic, simple, publicly available research tool such as a databank for MRI of brain with acute stroke is available. I have scoured the ends of the Earth for this. Any suggestions ? Thanks,
J Avasarala
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Thanks to ALL those who answered my query. I think Kathryn's suggestion that looking into one's own institution MRI data could be of tremendous help. There are no public datasets that are 'open' to the public.
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I have a series of data from MRI brain database in MNC & DICOM format. 
how can i open them in Matlab? Or how can i convert them into a jpeg ?
Thank you. 
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Hi
Are there any function to convert mnc format to nii or Analyze format ?
Thank you.
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I'm using TMRE 100 nM in hippocampal slices following OGD. I know that this dye can give a stronger or lower signal in polarized mitochondria, depending on its concentration. At 100 nM it should give a stronger signal in polarized mito. right?
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For those who are still interested in this topic: Do not forget that you depolarizes the cell by TMRE itself. If you use TMRE at very high concentrations, the potential inside the cell becomes more positive and the dye may flow out of the mitochondria again.
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Since Biological Parametric Mapping (BPM) is no more supported, I would like to find another tool to combine several brain images acquired for each subjects or different groups.
I saw fusion ICA but it is not convenient for my data....
any other idea ?
Thank you
Isabelle
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If you want more flexibility in your ability to combine modalities, I would suggest extracting your values from the voxels of interest and treating them like any other variable in traditional statistical packages.
If you provide more information about exactly what sort of combined data analysis you're trying to do, we can answer more specifically.
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Can you explain about it? Since software simulations have certain limitations, validation of new segmentation methods can be done using human-like phantoms, whose physical properties (e.g., geometry of the tissue structures and material properties) are known and are similar to the in vivo properties. The phantom images are generated using the MRI scanner and are more realistic than images generated with software simulations.
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It's typically used in mathematical formulations of the image formation process. Because it is computable using simple shapes for which the forward transform is known, you can exactly calculate the error in the reconstruction when computing the approximate inverse using your reconstruction method. Compare the approximate inverse (your reconstruction) with the Shepp-Logan phantom and you have a measure of your method's error.
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I want to know the meaning and usage of vivo.
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Vivo = living or alive. Usually in medicine we see the words "in vivo" which means an investigation is done "on living things" or we see "ex-vivo" which means an investigation is performed on something that has come from a living organism (like a tissue sample or biopsy for example)
Hope that helps
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I want to write a paper about MRI brain segmentation . Can you state your suggestions that I can use them to start working on this topic?
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Hi Sahar
I suppose, visualization and analysis of diffusion MRI data can be considered as the most significant problems in MRI brain image segmentation. I think, you should catch a glimpse at top research-published by nature communications 2018- in this subject. Maybe it can be helpful:
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When I am using the gray2rgb I get an error that it does not exist?
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Hello,
for this kind of image conversion I recommend using ImageJ (or FIJI) instead of Matlab. Much easier anf user-friendly...and free !
You can find imageJ here : https://imagej.nih.gov/ij/
and FIJI here : https://fiji.sc/
Good luck !
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I know magnetoencephalography (MEG) records magnetic fields-which are very small- produced by electrical currents in brain to map brain activities. how effective the external magnetic fields can be on the response? can we also use them (external magnetic fields) to change brains activity on a good way-such as improving memory?
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You answered your question. Yes, external magnetic fields affect MEG recordings and quite easily can make them useless. What MEG measures is extremely weak magnetic field induced from neuronal currents. Background (external) magnetic field is much stronger and it would be probably impossible to measure brain magnetic field if the MEG recording rooms were not magnetically shielded.
Regarding the second question, check out TMS (Transcranial magnetic stimulation).
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There are different types of diagnostic tests for Alzheimer's disease. as far as I know, one of them is positron emission tomography (PET) scanning. what exactly does cause the sign of the disease on a PET image? what percentage of Alzheimer's disease can be diagnosed by this procedure? do prescription drugs affect these signs after we take the test again?
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Hi,
Currently, International Working Group (IWG) and National Institute on Aging Alzheimer's Association (NIA-AA) has proposed several biomarkers as diagnostic criteria which includes cerebro spinal fluid (CSF) amyloid beta (Aβ) and tau, atrophy on MRI, glucose metabolism on [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) and fibrillar Aβ burden on amyloid PET.
There are few regions, which acts as definite Hallmark regions for AD. You could refer to below attached papers.
(11)C-PIB-PET for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI)
Structural MRI and Amyloid PET Imaging for Prediction of Conversion to Alzheimer's Disease in Patients with Mild Cognitive Impairment: A Meta-Analysis
18F-FDG PET for the early diagnosis of Alzheimer’s disease dementia and other dementias in people with mild cognitive impairment (MCI)
FDG-PET for Prediction of AD Dementia in Mild Cognitive Impairment. A Review of the State of the Art with Particular Emphasis on the Comparison with Other Neuroimaging Modalities (MRI and Perfusion SPECT)
Biomarker-based prediction of progression in MCI: Comparison of AD signature and hippocampal volume with spinal fluid amyloid-β and tau
Biomarker-based prediction of progression in MCI: Comparison of AD signature and hippocampal volume with spinal fluid amyloid-β and tau
I hope these article will help you.
Further, regarding the medication you could look into these articles
Drugs for Alzheimer’s Disease: Are They Effective?
Pharmacogenomics and therapeutic prospects in Alzheimer's disease
Cholinesterase inhibitors for Alzheimer's disease
Gud Luck !!!!
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How to find ROI from MRI brain image , perform segmentation and convert into 2d?
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Dear Minal,
There are lots of medical software tools, which are currently available for segmentation. For segmentation you can use SPM, FSL, Freesurfer.
You can draw manual ROI or by using atlas. Further, its mainly based on the application as parth said. What your ideally looking into.
For conversion of 3D to 2D you can use matlab coding
Thanks
Gud luck!!!
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I have an MRI brain image in Lab color space and I want to do contrast limited adaptive histogram equalization on L channel and then do k means on a and b channels.
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Dear All,
I am looking for an implementation of EnFCM (Enhanced Fuzzy C-Means) algorithm. I know it is not that difficult to implement, but I am looking for fast way. Kindly, if some one has information, share it here.
Szilagyi, László, et al. "MR brain image segmentation using an enhanced fuzzy c-means algorithm." Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE. Vol. 1. IEEE, 2003.
Thanks 
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To what extent do you believe that psychogenic amnesia is distinct from organic amnesia? What would be the differences and similarities between psychogenic amnesia and organic amnesia? 
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They are distinct in aetiology and also typically in both severity and reversibility. Organic amnesia is the product of a brain lesion, and tends to be severe and disabling, and usually irreversible. Psychogenic amnesias are rarely severe or disabling, and in most cases reversible as there is no associated brain damage.
I would recommend reading introductory Cog Psych textbooks, such as chapter 7 of Groome et al. (2013) An Introduction to Cognitive Psychology: Processes and Disorders. Psychology Press.
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What are the current research areas and challenges in brain image segmentation?
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One challenge is with the acquired data going into segmentation algorithms; usually resolution and tissue contrast are too low for most algorithms to accurately identify many small subcortical regions and subregions. However, for the future, UHF + MP2RAGE seem to point in the right direction. A multimodal approach (additionally using T2, SWI, DWI, etc scans) is probably best if one can obtain them for each subject.
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What is chisquare attack and how do i perform chisquare attack for Least significant bit Image steganography
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The chisquare attack is a simble and famous method to test the Robustness of the security system against the attacks. It depend on probability analysis of stego image after put the information inside it using LSB method then compare it with the probability analysis of original image to check the difference between them. If the difference near zero it means no information inside the image otherwise if near one it means the image held the information.
Best regard
Zeyad Safaa Younus Saffawi
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What software or method could be applied for segmentation of hippocampus from MR DIcoms?
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It depends if you want just the identification of the hippocampus, or if you need subfield information. A number of free programs (e.g. Free surfer, FSL) will do a decent job parcellating the cortex and defining the hippocampus. If you need the subfield information Freesurfer does a good job (version 6.0, don't use any version earlier than that). 
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Dear experts,
I am new to rodents MRI image processing. I have two questions:
1. What is the best program for registering structural rat images and its diffusion Images to its structural atlases and vice versa? Is landmark registration a reliable method in this field?
2.Is it necessary to extract the rodent brain before registration? Does FSL-bet do the job?
Thanks for considering my question!
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Im not an image analyst but many of my colleagues swear by ANTs for registrations (see Avants BB, Tustison NJ, Song G, Cook PA, Klein A, Gee JC. 2011. A reproducible evaluation of ANTs similarity metric performance in brain image registration. NeuroImage 54(3):2033–2044 DOI 10.1016/j.neuroimage.2010.09.025. ) ; we used this approach for mouse brain images (See Wood, T.C., Simmons, C., Hurley, S.A., Vernon, A.C., Torres, J., Dell’Acqua, F., Williams, S.C.R., Cash, D., 2016. Whole-brain ex-vivo quantitative MRI of the cuprizone mouse model. PeerJ 4, e2632. doi:10.7717/peerj.2632). Finally, i believe it is not essential to extract the brain from the skull prior to registration, but if you wish you can try the program that my colleague modified from FSL-BET and posted here: https://www.nitrc.org/projects/rbet/
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There is the old IEEE article on MRI measurement of neuronal current by Dr. Ueno:
"Neuronal current distribution imaging using Magnetic Resonance" , IEEE Transactions on Magnetics, Vol. 5, No 35, 1999, p.4109
Now Bruker biospec resolution is about 30 micrometers in plane. Can we now make an image of neuronal currents in animal brain? Thank you for the articles.
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I am not a specialist in neurology but  I think that neuronal current is alternative current of some frequency (it is seen in EEG). The frequency is small and it gives a rise to J(0) (spectral density of magnetic field fluctuations at zero frequency). We know that only T2 (spin-spin relaxation time) is sensitive to this spectral density. So I have a question. Why do we not see neuronal currents at high field MRI. What "dwarfs" means? Could we use the method of T1 in rotation coordinate system ? Low field MRI is very unsensitive.
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Image processing and neural network
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Hi Mahmood,
As our colleagues say in their previous answers, it depends on if you are looking for "modality propagation" algorithms and the actual application of the synthesized pseudo-CTs. I would recommend to take a look at these papers as well:
I hope this helps.
Good luck!
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I would like to perform IVIM analysis of prostate diffusion-weighted images. Osirix UMM plugin doesn't work on my MacBook Air. Do you know alternative software?
thank you
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The Medical Imaging Interaction Toolkit (MITK, check links below) provides some IVIM analysis tools.
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I have some T2 hemosiderin images of a brain tumor and I need to know if I can use such images for finding out about relative blood distribution. Thanks for your help in advance.
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Hello,
This is technically not a true T2-weight image. This is a T2* gradient recalled echo image. It may have been labeled as "T2 hemosiderin", but that is just a arbitrary nonscientific name given to the sequence by the imaging center in which it was acquired. You cannot directly assess vascularity using this. It is tailored to show susceptibility and therefore just shows bleeding (or calcification). Now, one can say that more vascular tumors have a higher tendency to bleed, but nevertheless, it does not directly show vascularity. Some sort of perfusion imaging (there are many kinds) will be the way to demonstrate tumor vascularity.
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Hello all,
My question is whether positron emission tomography measures the binding of the radioligand to a receptor that is specifically located at the cytoplasmic membrane or to all receptors regardless where they are located in the cell. I guess it depends on the tracer physiochemical characteristics, whether it penetrates the cellular membrane or not, and on the binding site within the protein. I just need a confirmation from an expert. 
Thanks
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Furthermore, due to the resolution of PET you could not differentiate the binding site in a cell........
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I need to use blood signal intensity in T1 MRI as reference in my project about brain tumors.What I have, are slices of MRI for entire brain. Is it possible to define blood signal in T1 MRI of brain? Your help is deeply appreciated in advance.
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It depends if your T1 sequence is flow sensitive. If you have a flow sensitive T1 sequence, then the sagittal sinus intensity will not be equivalent to 100% blood volume. I'm guessing you want to normalize to estimate a blood volume. There are issues with tissue T1 intensities also. There are many reasons why this is a bad idea, though people do claim to do it all the time. If your goal is T1 relaxivity, that is a whole other technique.
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Dear all
We have a GE 3T 750w 
I have a problem with the contrast-enhanced MR angio of the neck (see screenshot)
- we have a ring, like a "donut" around the vessels
Sometimes it is difficult to exclude e.g. a dissection, notably of smaller vessels such as the non-dominant vertebral artery
We use the standard CE MRA sequence
Do you see the same "donut" on your CE-MRA? 
If not, which kind of sequence, and which rate of Gd injection do you use?
Thanks for your help - very much appreciated to improve the image quality !
Happy new year !
Sven
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i didnt find any such protocol-- 
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I've got a set of resting data and found activations outside the head. I realised that a very large FOV was used during acquisition. Can this affect connectivity results?
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thank you, Salvatore, very helpful
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Dear all
We have a GE 3T 750w 
I have a problem with a skin artifact(see attached images)
- may appear occipital or parietal (oftentimes more or less symmetric)
- appears 1mm iso-voxel 3DT1, evident on post-Gd (due to enhancement of epicranial structures
- appears more frequently on 32CH head only coil, and sometimes on 24CH head&neck coil
Is our scanner the only scanner with this problem? Or has someone seen this artifact as well?
Thanks for your help - very much appreciated to find the origin of the problem!
Happy new year!
Sven
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Yes, Gd images only
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I have a set of data (325 repeated slices) of Perfusion MRI with specific TR and TE (but I don't know what kind of perfusion (DSC,DCE or ASL) it is!). Does any one knows what I can get from these images? is it possible to obtain CBV maps from them? Indeed, I need to get information about blood distribution in a tumor; do you think that I can use these images?How?
one of the slices is attached.
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Hi Nargess,
Short answer to your question:
Yes, you can. You will have to find out what Perfusion technique it is to make the best use of it and also you will need to 'read' 'delay time' between these images for a particular slice to process it correctly.  
You will find answers to most of your questions here:
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Hello,
I have just started researching about brain imaging techniques for early Alzheimer's Disease - something I know little about at present. It is often stated that short term memory is the first area that is affected for the patient. However, is there any research into how often this is actually the case, and how often it isn't? I haven't come across any so far in the literature I read. It is just often stated that it is the first sign, but I want something more substantive than that.
Short term memory from an imaging point of view, can be assessed by monitoring changes to the hippocampus. I am therefore investigating the existing techniques, and also seeing whether or not they can be improved on in anyway using my experience of imaging for other neurological conditions.
Kind regards
Alexandra
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Tests that measure the sense of smell may soon become common in neurologists' offices. Scientists have been finding increasing evidence that the sense of smell declines sharply in the early stages of Alzheimer's, and now a new study from the Perelman School of Medicine at the University of Pennsylvania published today in the Journal of Alzheimer's Disease confirms that administering a simple "sniff test" can enhance the accuracy of diagnosing this dreaded disease.
The sniff test also appears to be useful for diagnosing a pre-dementia condition called mild cognitive impairment (MCI), which often progresses to Alzheimer's dementia within a few years.
Neurologists have been eager to find new ways to identify people who are at high risk of Alzheimer's dementia but do not yet show any symptoms. There is a widespread consensus that Alzheimer's medications now under development may not work after dementia has set in.
"There's the exciting possibility here that a decline in the sense of smell can be used to identify people at risk years before they develop dementia," said principal investigator David R. Roalf, PhD, an assistant professor in the department of Psychiatry at Penn.
Roalf and his colleagues used a simple, commercially available test known as the Sniffin' Sticks Odor Identification Test, in which subjects must try to identify 16 different odors. They administered the sniff test, and a standard cognitive test (the Montreal Cognitive Assessment), to 728 elderly people.
The subjects had already been evaluated by doctors at Penn with an array of neurological methods, and according to expert consensus had been placed in one of three categories: "healthy older adult," "mild cognitive impairment," or "Alzheimer's dementia." Roalf and his team used the results from the cognitive test alone, or combined with the sniff test, to see how well they identified subjects in each category.
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There is increasing evidence that global brain signal measured by resting-state fMRI contains potential physiologic basis. My question is, how to characterize the global brain signal, can it be achieved by computing the mean amplitude of low frequency fluctuations? Or other ways?
Is there any toolbox/software available? Thanks in advance.
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Lei Gao I believe you want to obtain something like percent signal change in resting state fMRI - not connectivity, or proxies, etc. but actual BOLD.  The problem is you do not have an implicit contrast in the resting state as you would in task related data.  Perhaps look at ALFF or fALFF type of analyses?
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Would like to know the feasibility and actual depth (areas of the brain) which could be reached with rTMD
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Dear Peter, as far as I know TMS acts by inducing an electrical field in the brain (i.e. spatial distribution of voltage) which in turn will produce electrical current depedning on the resitence that it finds. It is thought therefore that large collections of CSF may facilitate the presence of induced current. It has been long thought that in the interhemispheric fissure an efficient current could be developed in deeper structures than in the brain parenchima, probably due to the width of the inter-hemispheric sulcus. In older literature the induction of phosphenes was taken as a good measure of how deep stimulation can go in the inter-hemispheric fissure. Indeed, given the peculiar distribution of the retinotopic representation in V1, the wider the angle of the phosphene, the deeper you go with TMS. According to this view, depth of stimulatn was considered as much as 4 cm. This has been however challnged in recent work on the possible origin from extra-V1 (V2 and V3) cortices of TMS-induced phosphenes. In other words, there is little empirical data that can answer your question. You may find several works claiming that supplementary and pre-supplementary motor areas, with compatible behavioral effects. Putting together these data it seems that with conventional figure-of-8 coils you may reach as far as around 2 cm from the brain surface (my opinion! Not demonstrated!) You probably may find a better answer looking at the literature on modeling the electrical current (not electric field) in realistic brain models, whcih unfortunately  don't know much about. Good luck.
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Hello, 
We have a philips 3T achieva resonance and we are doing a sequences to use NODDI and HARDI with:
- b= 400 (15 directions)
- b=700 ( 30 directions)
- b= 2800 (65 directions)
We generate the gradients in the whole sphere with a program that obtain the optimal. And we have b=0 interleaved every ten directions.
The question is what is the best parameters to do that? I mean voxel size, TE, TR, use SENSE, gradient timing, EPI factor, ...
We tried with 2.5 isotropic voxel size a we obtain a value of one of SNR (same voxel size in reconstruction and acquisition) But when we used a voxel isotropic size of 2 (2x2x2) the SNR decrease a lot and the size in reconstruction and acquisition are different in the resonance.Perhaps obtaining the perfect combination of parameters we get a good sequence.
So we have a lot of question. What voxel size should we use? On the other hand, should we have the same size voxel acquisition that voxel reconstruction?
What TE, TR, EPI factor, gradient timing... are best?
We use SE sequences and EPI readout but there are other sequences (SE, IR, MIX, FFE) and different scan mode (SE, STE).
Thank you very much.
Best regards,
Ana.
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Hi Ana.
It is not surprising that your SNR is decreasing drastically when you go from 2.5mm isotropic to 2mm isotropic as your resolution (cubic) is roughly half (i.e. 2 x 2 x 2 = 8mm3, and 2.5 x 2.5 x 2.5 = 15.625mm3). Acquiring 2 x 2 x 2 would be great, but 2.5 x 2.5 x 2 .5 would also be acceptable as long as you have good SNR. What sort of brain coil are you using?
I have done a lot of multishell MRI... Instead of bvalues of 400, 700 and 2800, I suggest you use 700, 1000, and 2800, with number of directions (for example) as 20 (b=700), 45 (b=1000), 75 (b=2800). This will create data suitable for HARDI and NODDI.
I think interleaved b=0 every 10 directions may not be necessary. Instead, interleaving them every 20 volumes should be enough.
Are you using multiband? If so, try using a factor of 3 or 4. In terms of acceleration, I suggest you use a factor of 2 (using a higher acceleration factor will result in substantially reduced SNR, and possibly artifact in the midline structures). Does your sequence have CAIPI? It makes a huge difference to the acquired data.
Are you also acquiring a quick (6 direction) blipped (reverse phase-encoding) sequence? Then you can correct for distortions in the typical regions of EPI distortion (frontal and temporal) using FSL's topup module and then feed the output into eddy.
In terms of TR/TE etc, that is something you will have to work out as they will be different for every sequence and scanner.
Regards,
Jerome 
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To define it as spontaneous production, the selection and the execution of new auditory-motor sequences appears insufficient. On the other hand, compared to numerous brain imaging studies on musical cognition, perception and musical development, there are few of them on musical invention which are, for the most part, confined to the study of already memorised performances and very few on musical improvisation in real time. In a brilliant work, a number of years ago Limb (2008) asked ten pianists to memorise a melody and, after having them lie in the tube of a suitably modified magnetic resonance machine and connected to a keyboard, he managed to have them reproduce a melody they had just learned, make a simple scale and, finally, improvise. Limb saw that the improvisation was correlated to the activation of a nerve network that included, among other things, structures such as the inferior left frontal gyrus, the anterior cingulated cortex and the medial prefrontal cortex. The most interesting evidence was the widespread ‘turning-off’ of the prefrontal areas, which are generally correlated to the conscious control of the activities in progress and responsible for interference in the capacity to concentrate. This experience of ‘turning-off’ is not yet sensorial and not yet perceptive; it is not an experience of emptiness, but corresponds to the activation of mental images that anticipate the specific action that leads to an internal emulation of the planned motor actions, very similar to what takes place in reality. As has been shown recently by Ridderinkhof and Brass, (2015), also with reference to the sphere of football, the comparison between the effects of the anticipated action and those of the internal emulation may generate an error signal that may encourage the improvement of the motor performance, even without the execution of the real movement.
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Dear Ubirajara,
thanks for your suggestion. Unfortunately I don't know the Bob Snyder's book "Music and Memory", but I'll try it. In my opinion, our brain, more than a reactive machine (as yet it was stated for a long time), it is a predictive machine, that formulates hypotheses, provides the consequences of actions and plays in advance. The evolution of motor schemes of behaviour has given rise to an natural logic underpinning prediction and action. In his long adaptive challenge, the human brain not only tuned systems for fast action reshaping, but also molded the entire musculoskeletal architecture and redefined the internal models of the body. 
In the original form of life that is jazz, narrating means directing time: a time of epiphanies and introversions, of intuitions and revelations, of syncopated rhythms and aesthetic insights, which appear and disappear on the edges of interference between consciousness and the unconscious.
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i am working on feature extraction of MRI brain images for classification in normal and abnormal(having tumor) image. i need a MRI brain database (T1 or T2) of atleast 100 healthy patients as well as patients with tumor. please send me the link to either purchase or download database.
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I recommend you to use the brain tumor database from the MIC- CAI 2013 Challenge on Multimodal Brain Tumor Segmentation. This is  a very good database of brain tumor (high grade an low grade) with segementation results and groud truth.
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I have a set of 22 brain images provided by MRI technique.
Now I want to compress them by JPEG 3D method. I am little confused with the method. Shall I compress every single image by JP3D method? if so, then what makes it different from JPEG2000 or JPEG method?
 Regards,
Keyvan
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i need information about FSL technique and scripts to extract features from MRI brain image to detect dementia
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Hi,
I'm guessing that you need features for classification purposes. If this is the case, you may consider using "texture features" instead. Within this group you have Gray Level Co-occurrence Matrix (GLCM) which has been used successfully for anatomical MR images classification. The following links may help you:
https://en.wikipedia.org/wiki/Image_texture (emphasize the Statistical Approach)
If you are familiar with MatLab.
Hope this is useful,
Paulo
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Hi all
I am doing some simulations of monitoring bleeding at the brain using a microwave technology.
I would like to move to a realistic data. (currently I am modeling the bleeding as a simple sphere)
Do you know where I can find some data sets that following up the bleeding size over days?
(I can find at the publications nice graphs that describing the hematoma size over days but I want the images themselves).
Thanks a lot
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Hi 
It is highly unlikely that you will find ready datasets for serial imaging of ICH. The investigators of large trials (like STICH) may have access to such data. Failing this, you would need to collaborate with a large volume neurosurgical center that manages such patients. You can extract information retrospectively using the ICD9 codes. Most patients with ICH are likely to have had at least 2-3 serial scans. So this would be a good way to go, IMO. 
Venkatesh. 
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Dear friends 
Do you know how to measure cortical thickness and cortical concentration in the MRI images?
what kind of moralities are usually used for this procedure to see plasticity? (T1 or T2 or FA etc ?)
which software is the best and most user friendly for this processing?
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Indeed, FreeSurfer was designed for this type of analysis in one simple command.
For a step-by-step tutorial on how to use it, please see my ebook:
Regards,
Jerome 
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I have f-MRI brain images(in .nii format). I wish to obtain all voxel coordinates as 3 columns with the 4th column giving the corresponding intensity value in float for observation purposes.
1st column :- X coordinate
2nd column :- Y coordinate
3rd column :- Z coordinate
4th column :- corresponding intensity value
Is there any software that can automatically do that ?
how can i extend this to ROI analysis ?
Your help is appreciated.
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Hello Prateek Bansal,
     I'm not sure if the fMRI coordinate you mentioned is from the statistically significant "blobs". If so, you could get the MNI coordinate (x, y, z) and intensity from the toolbox named SPM 12 or xjview embedded in MATLAB. 
     Furthermore, when you have the MNI coordinate, you could extract the intensity value by SPM12 (please find this function in the 'batch' label) as well.
     Please visit the following address for downloading:
     Good luck :)
     Hanna Lu
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I am looking for a reference for the first report of beta oscillations. Does anybody know of one?
Thanks in advance, Ben
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Here the credit should go to Hans Berger who in 1929–1938 published altogether 14 papers with exactly the same title "Über das Elektrenkephalogramm des Menschen". In which of these papers he for the first time mentioned beta I have not checked out but a drawing of beta is seen at least in his notes from 1931.
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I need to validate my method with previous method on brain MRI images, I am unable to find ground truth of images. most database do not provide ground truth. let me know if you have any idea
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Dear Shafiullah,
You need to state what your method or ground truth actually is.
If you want to know the ground truth for what a particular MRI looks like, try an MRI simulator, e.g.
If you do automatic anatomical segmentations, in addition to the ISBR data we have made ours (Hammers A, Allom R et al. 2003, Gousias IS et al. 2008, etc. - labelling methods Heckemann RA et al. 2006, 2010) available, too:
Unfortunately it is not possible to help you more specifically in the absence of more information!
Hope this helps a little,
Alexander
-----------------------------------------
Alexander Hammers, MD PhD
Professor (Honorary Consultant) of Imaging and Neuroscience
Head of PET Imaging Centre
Division of Imaging Sciences and Biomedical Engineering
King's College London
St Thomas' Hospital, London
Telephone +44-(0)20 7188 8364(PA Helen Hendy - Tuesday, Wednesday, Friday)
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Dear Experts,
How should I perform my analysis with probtrackx to obtain the number of voxels in the target mask that show connectivity to a seed mask? Something like the figure attached.
I have a small ROI as seed (2mm radius) and a single target mask that it is also waypoint and termination mask.
Thanks
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Hi 
If you want to use Probtrackx function from FSL, you can simply assign a seed mask and target masks (load as a text file). In the end, you can calculate number of voxels within the tracks connecting between the seed and the target using the output file. 
Here, they explain details. 
proj_thresh <list of volumes/surfaces> threshold
Best Regards,
Haemy Lee Masson
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Currently, I'm assessing the feasibility of collecting brain wave data during use of a mobile learning app. The NeuroSky head set isn't very costly, whereas the "research tool" is.
As far as I know, there is no review or test rating available for the research tool in combination with the head set.
Can you provide your personal experience with the tool and the app?
I'd like to gain knowledge in order to prevent from purchasing nonsense. Thank you very much in advance for your support!
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Hey Pia,
Before I start, let me put a disclaimer that I am a co-founder of a company that produces research mobile EEG devices. But I will do my best in replying to this message in an unbiased way.
The system depends on what exactly are you trying to measure. Generally, if you have an experiment that involves movement, it is very difficult to use dry electrodes, as they produce motion artifacts that are not easy (if not impossible) to filter out.
However, if your experiment is in a sitting position, then dry electrodes are good.
NeuroSky has only one measuring point on the forehead - this is generally not enough, since you cannot use data-driven signal processing techniques for artifact removal (like eye-artifacts) like ICA. So, Neurosky gives something out, but it is only useful in a very restricted setup. To make the Neuroscky contact better, you can put some conductive gel on the electrodes (I suggest Easycap, but there are also other producers, like Axelgaard). Finally, the samplinf frequency of Neurosky is 128Hz, which means that the bandwith is 0-64, which means you have the flat frequency response up to 30Hz at best, taking that their filters are well implemented. So... if you are not using gamma band, and you need limited beta, and you are fine with one electrode - that could be fine.
The next one (pricewise) is Muse. It is a better system in my opinion. It has 5 measuring points (I believe 2 of them are reference and ground and only 3 measuring electrodes, not sure). Everything is similar to Neurosky, except that their sampling rate is 220Hz, therefore allowing beta and part of the gamma bands. Three electrodes also allow for basic Blind Source Separation processing. And again, gel can improve the contact.
After them, there is Emotiv (they have Insight with 5 electrodes and Epoc with 14). Epoc has "semi-dry" electrodes, which means that their contact is better. Again there are problems with movement, because the electrodes "slip", so not great for outdoor studies. They have a sampling rate at 128 and 256, and claim the flat frequency response from 0.2 to 43Hz.
The problem with all of these systems is that they only provide a LIMITED access to raw data, which is generally a problem for scientific studies. Emotive gives the permission, but only with a specific licence (which than makes the system "pricey")
After Emotiv, there are research EEG systems, that I can separately elaborate on, but I believe they are not falling into the price range you are currently looking at.
About all these systems, I am not sure about their support for mobile phones.
I suggest that, before you buy one of the systems, you check with suppliers if they provide a full support for mobile phones (if you need it) and what data do you have access to.
In case you have more questions, and you believe I can provide you with a good answer, feel free to contact me, I will gladly help :)
Best wishes and good luck finding the appropriate system for your study! 
Bogdan
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I am wondering what are the ideal MRI scan parameters for both pre and postoperative DBS surgery for use with the software LEAD-DBS. I currently have postop scans that are not ideal and LEAD-DBS is having difficulty reading them. 
Our center uses a 1.5T with low SAR, but we are not opposed to increasing SAR slightly. 
Thank you,
Greydon
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You might want to take a look at published articles and see what scan parameters they use as a starting point. I am not familiar with the software specifically, but modifying locally accepted parameters is not a process to be taken lightly. Certain parameters (such as increasing TE) are likely to improve your lead discrimination without causing significant SAR changes, but this should be done with the assistance of competent local MR physicist help.
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I am using SPM to coregister MRI and PA brain images. How can I store the co-registered image displayed in graphics window as 3D image?
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Indeed, source and reference images need to be the exact same dimensions with exact same voxel sizes. Depending upon the software used to display the 3D rendering, the origin (0,0,0) often needs to be the same as well. I have always found InsightSNAP to produce the best renderings. My book (jeromemallershandbookofstructuralbrainmrianalysis.yolasite.com/ ) shows how to do this in Section 11. 
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Any Good MRI-CT DICOM Image Database including 1.Axial (Horizontal-Transversal), 2. Coronal, and 3. Sagittal Brain Images to use for my 3D Brain Image Reconstruction and 3D Segmentation Algorithms ?
MRI-CT Brain Images have to be from same person-patient and should include the following 3 Brain Views-Planes:
1.Axial(Horizontal-Transversal),
2. Coronal, and
3. Sagittal Brain Images
so that a Full 3D Volume Pixel-Interpolation Reconstruction Algorithm can be deployed and tested.
Any web-links are more than welcome.
Thank you.
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True, Matlab is slower than programming things directly in C++ or Java, it depends on what you want to do, create interfaces (C++) or analyse data (Matlab). But still, you could take the axial data, save as sagittal and coronal with Matlab and then run in whatever you want. Hope that helps.
Carlos
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I'm working on brain annotation of brain 3D MRI and in order to get the best result, the image enter must to be well segmented, so for that I’m looking for a software for automatic segmentation of brain  with tumor in 3D-MRI images 
or if anyone know any data base that has 3D-MRI brain images well segmented as BRATS.
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If you have multimodal MR images (T1, T2, PD etc), you could simply use SPM12's segmentation routine to do the segmentation. It gives rather robust results even without any need to manual adjustment.
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Hello everyone,
I would like to scan one short sequence (90 seconds) multiple times on one subject, and then co-register and average images to get rid of artifacts and motion distortions. Can you recommend some tool for this ? Is it possible with SPM12 ? Or should I do it in photoshop ?
Thank you for answers
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There are pros and cons for either FSL or SPM. Personally, I prefer the latest SPM12 version. The new user manual is easily understandable, but you need to be aware that you need a Matlab license to run SPM!
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i want a scanned images of brain for my research work,so that i can use for comparitive analysis
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http://www.mindboggle.info (manually labeled datasets for gray matter, white matter, atlases etc).
https://db.humanconnectome.org/ (the connectome project, hundreds of scans of multiple modalities, soon to release more data in summer).
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