Science method

Magnetic Resonance Imaging - Science method

Magnetic resonance imaging (MRI), nuclear magnetic resonance imaging (NMRI), or magnetic resonance tomography (MRT) is a medical imaging technique used in radiology to visualize detailed internal structures. MRI makes use of the property of nuclear magnetic resonance (NMR) to image nuclei of atoms inside the body.
Questions related to Magnetic Resonance Imaging
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The method I am looking for should be non-invasive and within the scope of MRI modalities.
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Why not start with serial observations on how the different forms of neuroinflammation develop, Sneha Majumder?
In possibly considering the famous pieces of evidence presented at www.ms-info.net on the best-studied kind of neuroinflammation?
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Which Thoracolumbar AO fracture subtype MRI would have the highest chance to change decision-making?
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A3 and a4 fractures in neuro intact patients may be classified as B2 injuries and change initial treatment. I think for A3 and A4 when considering non operative management an Mri is highly recommended.
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I have a T1 weighted MRI scan (please see the attached). It has regions of tumour+peritumoral edema. I am trying to develop mask images (.nii) of
1. CSF
2. white matter
3. Grey matter
4. tumour region
5. One single .nii file comprised of 1-4.
I need your expert opinions and recommendations on the best way to get this task done. Thank you in adavance!
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Hi, you would have to first create a mask image of the tumor using 3D Slicer segment editor or Mricron software (easy to use).
once you have generated a mask for the tumor area, use SPM12 segmentation method to generate additional mask (use the tutor template mask to edit that area out of segmentation process).Also combining the 4 independent mask in singe file you would have to use colorcode for each set of mask and use fslmaths command to combine them into single file. you have to make sure to carry out segmentation mask having same dimension as the raw data as lesion is going to be present in subject space not a template.
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We have data acquired in *.fdf format but unable to visualize it via typical visualizing software/toolbox like we can do for fMRI data. Please suggest me the toolbox, software or converter to visualize this data.
Thanks in advance!
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I assume that FDF files are data acquired on an Agilent/Varian scanner? If so, mrTools (https://github.com/justingardner/mrTools) contains a routine (fdf2nifti.m) for converting FDF files to NIFTI files. mrTools is a Matlab based fMRI analysis package. If you do a bit of Googling I think you can find other similar converters as well.
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I am trying to develop an automatic segmentation system for T1 and T2 MRI (via Deep Learning) whose goal is to segment different areas of interest:
- Scalp
- Bones
- Blood vessels
- Cerebrospinal fluid
- White/gray matter
In order to be able to extract surfaces and to make calculations with.
At the beginning, I was based on an unsupervised segmentation system inspired by the W-NET model (https://arxiv.org/pdf/1711.08506.pdf).
But this system seems complicated to set up for this type of images. So I turned to other (supervised) models like U-NET or V-NET. But this kind of model requires to have the segmented mask as ground truth.
I would like to know if you have knowledge of the existence of a type of dataset where T1 and T2 brain MRI could already be segmented manually?
I found the following dataset: MRBrainS (https://github.com/looooongChen/MRBrainS-Brain-Segmentation) but it is only the brain that is segmented, not the whole head.
Thanks for your help!
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For my research project, I generate some brain MRIs (T1w) and I have a recurrent issue with some non-zero voxels generated in the background. Note that generated images don't have skull. I would like to find a way or a tool for removing these artifacts. For example, I already tried with FSL-FAST, but all non-zero voxels are segmented as CSF even if they are clearly in the background. Maybe there exists some FSL-FAST options which may help me but I don’t find them…
Thanks in advance for your help.
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Hi,
maybe trying to run a despeckling filter to the images, removing features smaller than a certain amount of voxels?
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In cortical blindness, there is no RAPD, ophthalmoscopy examination is unremarkable. Cortical blindness (CB) can be reversible like CB due to occipital lobe epilepsy (treatable with medications), hyponatremia (treatable withn sodium administration) or it can be irreversible like bilateral extensive occipital lobe infarction.
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Cortical blindness is in the middle of two extremes, 1. Anton's syndrome where patient is suffering from CB but denies and says that I am OKAY so much so that he/she tries to attempt crossing through wall or closed door. 2. Malingering. In true CB it better to straight away go for MRI brain to save time for management.
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Hello everyone,
I am researching for a paper discussing cross-training to other modalities in radiology and was wondering which is the most common modality radiology technology choose? MRI or CT
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I agree with the previous comments; computed tomography is the most common because it is widely available and accessible.
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I have measured breast tumor size using different modalities CESM and MRI. I have also the size on Histology.
I have a table of paired Samples Test, and the Sig. is .037 MRI and .523 for CESM when compared with the gold standard of histology. What does this mean??
Help xx
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The output table shows the degrees of freedom (df). The table also already tells you which modalities specifically differ. Please see my previous comments.
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The research is based on medical domain aiming to find Epileptogenic Zone in drug refractory patients. The study uses already recorded Scalp EEG and MRI of patients for analysis to find the Epileptogenic Zone. I was thinking of considering 50 patients data for this study, but how do I justify this number?
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Thank you Sir.
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Related to early diagnosis of Alzheimer's by deep learning
I'm trying to implement a deep learning model to classify stable and converter MC
.
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I wish to conduct a study involving the geometric morphometric analysis of entorhinal cortex and hippocampal shape variations. As I hope to acquire MRI scans from online databases, I would just like to ask if there are any recommended MRI parameters that accurately capture the overall shape of these two structures. For example: would it be more ideal to gather T1-weighted or T2-weighted images, and what imaging plane (e.g. axial, sagittal, coronal) would be optimal for viewing these structures?
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How make suspension solution of iron oxide nanoparticles for used as MRI contrast agents and dose of iron oxide nanoparticles which injected for each rat
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it depends on your SPION properties including longitudinal and transverse relaxivity. Most SPION, especially with a core size above 5 nm, is a T2 contrast agent and if you have an ideal SPION, then a lower concentration of SPION is needed.
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Can anyone help to put the right parameters in the search area on ADNI webSite
I tend to use PET and MRI as fused modalities to classify AD
MRI subjects must have PET
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Pleasure Guelib Bouchra
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Dear all
Has anyone an established and optimized protocol for a 3T GE 750w MRI?
Ideally, I would like to have a 2mm iso-voxel DTI with 30 directions
Thanks !!
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Thanks for the answers ! In the meantime I have changed my job, and now work with another vendor :-)
Sven
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Please share some useful techniques for feature extraction from MRI images.
If possible, add some valuable links to your suggestions related to code in python or matlab.
Thanks in advance.
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Hello,
Our research group has developed and uses Pynovisão for feature extraction and processing with machine learning and deep learning algorithms. For feature extraction we have implemented: Color (HSV, RGB), texture (GLCM (gray-level co-occurrence matrix, Gabor filter, LBP-local binary patterns), Shape, and Gradients (Hu moments, HOG - histogram of oriented gradients). We have used this software for MRI images in a paper in press.
The Pynovisão is available at: http://git.inovisao.ucdb.br/inovisao/pynovisao
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Dear All,
Can anyone guide me how to create 3D models of human flesh/skin adjoining human bones using CT or MRI data using segmentation method? Which tool is to be used to process such medical imaging datasets for soft tissues MRI/CT scan data?
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Hi, I'm sorry because I'm not sure if you mean exterior flesh as in skin. If that's the case then CT would be fine. If you're referring to ligaments, which attach bone to bone then an MRI is generally needed.
For example, I've attached two images, the first is a CT scan of a knee (named Knee CT). It's not my scan (I don't own it and did not perform the scan), but it gives you an idea of what you can see from a CT.
The second is a knee scan I've personally worked with in 3D slicer, this is an MRI scan ( named Knee MRI) and you can see the difference. In the CT scan you cannot really visualize the ligaments, while the MRI makes them very easy to see. They are there and you may be able to make them out, but it will be work to do it that way.
Again, I assume there is a slight language barrier here, so hopefully i'm answering the question you're asking. If not, just let me know and I'll do my best to explain further. Best of luck!
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I need help please
I have executed these commands to read the MRI images with extension nii:
[V,info]=ReadData3D;
imshow(squeeze(V(:,:,round(end/2))),[]);
I have run the code on the four module (T1, T1ce, T2, Flair) and also on the segmented images (ground truth). The black images still appear. For person number 1 (as an example), image 66 for this person, the resulting four non-segmented images are shown in attach, and they are not black. However, the resulting segmented image is completely black, why???
Where is the error in executing the code?
Regards,
Asmaa
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Hello
1. Change the image format.
2. Modify the modules.
3. If the image still encounters an error, you certainly did not observe a point in the defined code section, it will probably explain the reason for the error in the error section.
In the ([]) imshow field, set the resolution value range, put a number that may be so low that the image is completely dark, for example, write imshow (squeeze (V (:,:, round (end / 2))), [4000]).
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1. What are the multilevel diseases that identify with help of scanning images? Such as diseases that identify from MRI, X-ray, CT scans.
As examples, I can say Breast cancer, Chronic liver disease.
2. Where can I find the image dataset for that disease?
Any ideas and suggestions are much appreciated🖤
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The role of imaging in diagnosis of disease is quite extensive.
Esp in fields of oncology where in the not only in diagnosis but in pre operative planning, during the CCRT or in follow up of these cases, imaging is an important paraphernalia in management of the patients of malignancies like breast, colorectal, sarcomas, Musculoskeletal, gynecological as well as CNS malignancies.
The list is not exhaustive.
Regards
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Please suggest..
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X-rays are enough for identification of arthritis. MRI would help to identify early arthritis and more importantly soft tissue problems.
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Medical Imaging.
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Hi,
Have you already found the answer to your question?
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Hello,
I'll start my PhD next month and I will be mainly working with EEG. As I've never worked with EEG (only MRI) I was wondering if the community can recommend an (kinda) up to date Textbook on EEG. I'm mainly interested in the physical, biological and mathematical foundation of EEG recordings as well as the analysis of EEG recordings.
Thank you very much 🙏
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EEG pearls
Atlas in pediatric EEG
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I want to find the fetal brain MRI dataset for cnn model and deep learning.Can anyone help me, thank you very much
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For fetal brain 3D MRIs with manual segmentation, you can have a look to:
- the FeTA challenge 2021 dataset
- the spinal bifida spatio-temporal atlas
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Hi All,
I am looking to download 3T T1 MRI longitudinal data from publicly available databases for healthy subjects aged 18-55.
Can someone suggest such databases from where I can download the data ? I am not inclined to download data from HCP as my disease cohort was scanned on older 3T scanners.
Many thanks
Ri
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You can check the IXI dataset, it contains 600 3D MRIs of normal healthy adults including T1 MRIs.
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Hello.
I'm working on a study by using difussion weighted images of the brain.
The goal of the work is to generate tractographies. We realize we need to have all the images involved (labels, white matter, etc) at the same shape. And now by looking on some procedures with MRI images, normally they have to be registered to a standard template. So, my question is Should we have to register our DWI images to a certain template before to process? Because I was looking to register all the other images (labels, white matter, etc) to the dwi structure since dwi contains a 4D image which would be more difficult to process. But I have this doubt. Please someone with experience would answer the question.
Thank you
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One minor point: If you plan to use ROIs for tractography that are considerably small already in template space, transformation of these ROIs to subject space could effectively remove any ROI voxels due to (normally) smaller voxel sizes in subject space and the transformation itself. This could be one of the rare cases to transform the DWI data itself to the template space, but as Jerome Maller mentioned, the proper correction of the bvec tables is important.
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Dear Colleagues
We injected CT26 cells into rats' flank (s.c) to induce colorectal cancer. What biochemical tests do you suggest (sensitive ones) to ensure that animals are bearing tumors? I mean, is it possible to ensure with high blood glucose, FOBT tests, etc., that animals have colorectal cancer before doing sophisticated techniques such as PET-Scan or MRI (mainly because of their cost). We finally will do them, but we just weren’t to be ensured that animals have a tumor. I should mentioned that after 10 days of CT26 injection no macroscopic sign is detected in animal so far.
Thank you for sharing your experience
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Unfortunately, there’s no reliable way to do this with any current biochemical method.
Hopefully, this will become possible in the future.
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I´m using ITK snap in order to segmentate some structures in a MRI volumen. I want to take this segmentation and overlap into a new secuence of MRI (the same patient) to get some values.
I don´t know if that is possible and I don´t know if it´s possible to change the multiplanar reconstruction and then overlap it.
Thanks a lot for you time!
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thanks a lot! I´ll try it for matlab.
Otherwise, there is any way to do it directly in ITKsnap or another segmentation program (Osyrix, Horos, 3DSlicer)?
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I am implementing GLCM on MRI images. And also have got its features, & got the results too, but I don't understand the significance and utilization of all the features like entropy, contrast, etc. I know definition and equations, but want to know how to utilize all these features for classification and get the result.
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I used the GLCM along with the LBP to classify vegetation density from RGB satellite images please reefer to this study:
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Sometimes the advance technologies like CT Scan and MRI are available. But the competency to read the results is lack. According to big data technology, is it possible to construct "translation machine" or "scanner" for CT Scan or MRI "graphs/ pictures" into diagnostics statement that can be understood for the common ones ?
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Thank you for your information Rafal Z Slapa
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Dear Research Community,
I need to write full research protocol and I need help in suggesting the steps to follow and the template for it please,
your guide is much appreciated
Mohammed Abed, MD
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Driss Benattabou
Thank you so much
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Hi,
I got T2 images with less dark contrast. please give your valuable suggestions
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I got image like this
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I did obtain a 19F / 1H NMR probe that changes the signal in pH range 3-4. By adequate modification, I can change the range of response up to 2-0.5 or 5-4. My question is what could be a potential application of such a probe. Until now, I wanted to use these probes in MRI, however, there is a need for changes in pH 7-6.
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This would be a great question to post in our new free medical imaging question and answer forum ( www.imagingQA.com ), there are a number of MRI / MRS experts in the community. If useful, please feel free to open a new topic at the link below :
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Where can I download the datasets used by ISLES challenges regarding stroke Lesion segmentation? It has not been possible for me to get it from its website. Or any other public dataset about this subject.
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Service Unavailable Reza Amini Gougeh
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Hi
I'm working in Diagnosis Location  of aphasia lesion of  Stroke patients and I need to  database of MRI images for aphasia Patients.
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Hi Driss,
You could check out the free datasets listed on www.imagingQA.com at the following link :
If you don't find what your looking for, its free to join so please open a new discussion topic (there are lots of data scientists and imaging specialists in the community) :
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Is it possible to perform 19F MRI scans using devices already in clinical use for 1H MRI?? What changes should be made to make it possible? I will be grateful for the publication on this topic.
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Olaf Dietrich, on a non-clinical scanner you could probably try something like that. But you most likely would not be able to tune the 1H transmit coil to the 19F frequency, without at least replacing capacitors. Trying to pulse at the 19F frequency without re-tuning, will result in a large amount of reflected power which will either trip the safety system that protects the RF amplifier or damage the RF amplifier.
On a clinical scanner, I doubt the scanner software will permit shifting the transmit frequency that far without an x-nuclei license. If you are able to, the prescan should detect that the transmit coil is not tuned and cancel the scan (and probably give you a pop-up window saying the RF coil is damaged).
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for a project I want to create a 3D CAD model of the child's chest.
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google search
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Dear all,
does somebody know a good (and free) database for normal brain MRIs?
I would appreciate your answers. Thank you!
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Thank you very much all those who have helped me.
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Hello there!
I have searched everywhere for a MRI dataset for amyotrophic lateral sclerosis, ideally a multimodal one (DTI especially would be appreciated).
Thank you in advance.
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This would be a great question to post on our new free medical imaging question and answer site ( www.imagingQA.com ). We have a number of image analysis experts in the community. If useful, please feel free to open a new topic at the link below:
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Does anyone know where one might find an MRI compatible optical or infrared video camera which could operate inside the bore of a 7T system ? Preferably < $2k
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This would be a great question to post in our new free medical imaging question and answer forum ( www.imagingQA.com ), there are a number of MRI experts in the community. If useful, please feel free to open a new topic at the link below :
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I need it for a machine learning use not for a medical use
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Try American society of radiology website
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The patient is suffering from typical liver failure symptoms from three months. In CT scan and ultrasound liver seems OK. The blood test looks normal except low creatinine and prolonged aptt, blood gases reveals PH 7.5. reveals alkalosis.
MRI head scan reveals lesions in Corpus callosum. Looks like demyelinating process.
Is liver biopsy only way for diagnose?
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Although elevated ALT levels often signify ongoing hepatic inflammation, many patients with chronic liver disease and progressive fibrosis may have average values. Thus, a “normal” aminotransferase value does not exist in clinical medicine.
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Can anyone help please?
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You can find what you ask for in databases like https://portal.brain-map.org/explore/toolkit/neuroimaging OR you can use the healthy hemisphere for control
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If I report a breast imaging exam (MRI, US or Mx) which not shows any malignant findings in a biopsy-proven breast cancer, which BIRADS score do you use?
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BIRADS 3 ( Suspicious lesion)
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hello everyone!
is someone using an MRI compatible touch tablet? and where do you get yours from?
I read that many studies used that one from Tam et al (2011), but somehow I am not able to find any shop where to purchase it or to get any more details about it.
Best,
Adam
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dear all,
thank you for your answers. i believe I was a little bit naive, thinking this technology would be more accessible by now :)
we managed to change out setup, so a touchpad is not necessary anymore.
thanks
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In this regard, I'm looking for a CT/MRI dataset required to train a CNN model for medical image segmentation.
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If the existence of a pathology does not matter you can use TCIA .
You can find any kind of data set in there and I assume it is free
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Gradient strength vs gradient amplitude. Is a 3T scanner with reduced gradient strength but higher amplitude as good?
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Generally when a vendor gives a spec for gradient strength, they are referring to the maximum gradient an individual gradient coil can produce. However, as Samuel mentioned there are 3 gradient coils(X, Y, Z), if you pulse them simultaneously you get a gradient along the diagonal that is stronger than what any of the individual coils can produce. if you pulse the three gradient coils at 45 mT/m, the gradient along the diagonal would be 78 mT/m. So the vendor advertising this vector amplitude, is trying to make it sound like their gradient coils are stronger than they actually are.
Maximum gradient strength really only matters for DTI. The higher your maximum gradient strength, the larger the maximum b-value you can achieve at a give TE. Or conversely you can achieve the same maximum b-value at a shorter TE, if you have stronger gradients. The shorter TE means higher SNR. For DTI experiments, you want to use the same b-value in many different directions, so the maximum gradient strength of the individual gradient coils is the important number. For the system you have mentioned, 78 mT/m can only be achieved for 3 direction.
For other demanding pulse sequences, such as EPI, the gradient coil slew-rate is much more important than the maximum gradient strength. The optimum gradient amplitude for typical read-out gradient pulses or slice selection gradient pulses, is usually well below the maximum gradient that available gradient coils can achieve. However the slew-rates are all software limited in order to avoid peripheral nerve stimulation, so the vendors don't talk much about slew-rate.
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What MRI modality could give the best visualization of facial soft tissues? I use T1-weighted images currently, but the quality of some studies is pretty poor (even after denoising and intensity inhomogeneity correction). I've noticed that PD-weighted images could be more suitable for my purpose which is facial soft tissue thickness measurement. However, I cannot find any proofs that support my point of view. The other thing is acquisition parameters that have potential to increase imaging quality and soft tissue recognition. Where can i read about it?
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Hi,
With surface coils, the image will be of better quality. I recommend SE T1W, FSE T2W, PD, STIR/ T1W FAT SAT and DWI. Anatomical detail is good in SE T1W sequence, while T2W and PD sequences show pathology well, DWI and fat-suppressed sequences provide better characterization of pathology.
Contrast-enhanced imaging is absolutely necessary in patients without contrast allergy.
Technical parameters; TR 5000-6000ms, TE 80-110ms, NEX (AVRAGE) 7, matrix
192x192, section thickness 5.0mm/1.0mm (10-20% GAP), FOV 210-230, phase direction A>P, b value 0-800/1000 should be preferred as.
Hope it helps, have a nice day
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I would like to research on MR images (0.5T and 3T). Can you please suggest some websites that I can download dataset including both 0.5T and 3T MR images? Thank you.
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Try searching the image dataset library here :
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Since the nature of the noise in k-space is additive before reconstruction, can we exploit deep learning to denoise MRI this way ?
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I designed an algorithm for MRI data denoising which has good properties under heavy Rician noise (sigma is greater than 80). The method was tested on Brainweb's phantom and Matlab's ricernd() function. Now I want to test the algorithm on real MRI data. Could I ask you to recommend free datasets of MRI data where images are disturbed by heavy Rician noise (sigma is greater than 80)?
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Dear Krzystof
Are you interested with a test data with high b-values weighted diffusion MRI ?
matrix size of 196×196×16 (field of view=2.7cm×2cm×1.2cm)
native resolution 0.137755102 x 0.102040816 x 0.75 mm
31 b-values :
6 independent directions
As the b-value increase the signal decrease , then the SNR decrease but with 31x6 equivalent estimations of the noise baseline level
Images of animals. One hemisphere with high SNR, the contralateral has less signal, in the same image (pathological model).
You should have the noisy to ultra noisy image you want to deal with.
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By looking at a medical image, how can i identify whether it is an ultrasound or MRI or CT image?
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For preprocessing of PET or MRI...
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I know that training neural network models in Python is up to 15% faster compared to that of R.
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We normally see the elevation of serum or CSF neurofilament light (NfL) in people with Multiple Sclerosis (MS) and this elevation is correlated with MRI results such as demyelinating lesions in the CNS. Now, I would like to know is there any evidence out there that there is a normal level of serum/CSF NfL but MRI scanning is showing a lot of lesions in people with MS.
Thanks in advance,
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The value of sNfL as a sensitive and clinically meaningful blood biomarker to monitor tissue damage and the effects of therapies in MS, so i think , if there is active lesions in MRI, the serum and CSF NFL will be abnormal. we need to study this important correlation on our patients with MS
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Does anybody know a Matlab code for multiple sclerosis (MS) detection from MRI images using Convolutional Neural Networks (CNN)?
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Good morning, any news?
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MRI, fMRI, EEG etc..
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Hi,
PET scan with radio tagging of molecules has been used to identify the density and distribution of specific groups of neurons, mostly in pharmacodynamic studies..This has been employed on Dopaminergic neuron distribution and density in Parkinsonism and Schizophrenia.
Probably you will get leads from some of these articles:
Falkenburger BH, Saridaki T, Dinter E. Cellular models for Parkinson's disease. J Neurochem. 2016 Oct;139 Suppl 1:121-130. doi: 10.1111/jnc.13618
Tomasella E, Falasco G, Urrutia L, Bechelli L, Padilla L, Gelman DM. Impaired brain glucose metabolism and presynaptic dopaminergic functioning in a mouse model of schizophrenia. EJNMMI Res. 2020 Apr 17;10(1):39. doi: 10.1186/s13550-020-00629-x
Bossert I, Marinelli L, Castaldi A, De Carli F, Campus C, Abbruzzese G, Nobili F. Brain (18)F-DOPA PET and cognition in de novo Parkinson's disease. Eur J Nucl Med Mol Imaging. 2015 Jun;42(7):1062-70. doi: 10.1007/s00259-015-3039-0
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I'm working on MRI Alzheimer images, where can i get free datasets for my research work?
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Welcome Bharathi Ak
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For basic time-intensity-analsis (TTP, MTT, MI, Slope...) on MRI images eg. of the liver, vessels and the lung, I am searching free or open source software for PC or OSX.
Beyond these basics, desired features are:
- ability to directly import dicom images without prior conversion
- calculations using an arterial input function
- simple algorithms for motion correction or registration
Although not a free platform, are there plugins for OSIRIX?
I would very much appreciate your suggestions.
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I've done similar DCE-MRI evaluations with "3D Slicer" <https://www.slicer.org/> using the "MultiVolumeExplorer", the "SegmentEditor", and, for the actual evaluation, the Module "PkModeling" <https://www.slicer.org/wiki/Documentation/4.10/Modules/PkModeling>.
An alternative might be MITK <https://www.mitk.org/wiki/The_Medical_Imaging_Interaction_Toolkit_(MITK)> with the MITK-ModelFit module (may require building MITK from source to include this module).
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What type of computational infrastructure (laptop, workstation etc.) is necessary for MRI analysis?
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Dear Nelson,
You need high computational power for the analysis of MRI images. Such as: with Intelr CoreTM i7-8700k CPU 3.20 GHz, 32GB RAM and GeForce RTX 2080 8 GB.
Thank you!
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A 45 years old woman presents an epigastric discomfort . She denies using oral contraceptives or anabolic steroids. At CT and MRI with contrast were observed multiple non-steatotic adenomas ( total of 12 lesions ) ranging between 0,5 and 10 cm in both hepatic lobes.Three in left lobe and two in right lobe presenting more than 5 cm of diameter. The histological analysis excluded any malignization and confirmed an inflamatory adenomas. What is the best approach? Observation or resection only for those bigger than 5 cm? If resection is indicated -is the better option an anatomic left lateral sectorectomy and right enucleation or multiple enucleations in both lobes? Open or laparoscopic?
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By MRI with contrast study
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Hello everyone,
I need to annotate the MRI images (with .nii.gz format). Each image includes several slices. What I need is an annotation tool that can annotate the area of interest and propagate it in all slices? (considering that the location of object changes in different slices).
Thank you all in advance.
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I would recommend looking at these two tools:
  • ITK-SNAP (http://www.itksnap.org): This is a relatively simple tool to use for segmenting images.
  • 3D Slicer (https://www.slicer.org/): This is a very versatile tool with an active community and a sizeable selection of plug-ins.
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I used ITK-SNAP to segment out the cortex of mice from the MRI images. I would like to see if there is any difference in volume of the cortex pre and post treatment. Is there any software that is recommended to do such an analysis?
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hey segmentation expert there a way to compare stl image of root canal volume of a lower six exporeted from itsnap in a way that i can compare geometric changes
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Hi everyone,
I was wondering if anyone could help me with the implementation and visualisation of DICOM overlays.
In particular, I would like to be able to visualise a dicom image (say an MRI image) with a certain dicom overlay (say a mask) on top of it. The ideal final result would be something similar to an alpha transparency.
1. Is this possible to do it with some DICOM viewer, keeping the two dicoms (the MRIimage and the mask) separated?
2. Or is it necessary to include the overlay in the MRI image dicom fields 0x60xx? In this second case: how is this done? The documentation about it doesn't seem too clear to me.
Any suggestion is welcome,
Many thanks,
Alberto
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Hi, you may use mango Dicom viewer and can add overlays on Dicom.
here is the link
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The question arose during analysis of two of our datasets, both under 3T
One study data I have has p50 intensity around 20000
Another one has an intensity in 3 digits (500 ish)
When looking for public datasets, the intensity are roughly ranging from XX to XXXX, but can't quite find one where intensity are in 10k+ range.
My question is:
Some of the previous studies (eg. ) mentioned that signal intensity does not matter as long as they can be used to distinguish conditions. However, I was wondering what's the impact of the intensity on the result?
Or was the data collected is simply wrong
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I second Allen's response that raw MRI signals (including BOLD fMRI) are generally arbitrarily scaled and do not have a direct quantitative meaning. For this reason, percent signal change is more meaningful in BOLD studies (although it too is not a direct measure of a single physiological process).
One thing I would add is that the absolute value does start to become meaningful in the context of signal-to-noise ratio (SNR) or temporal SNR (tSNR). tSNR is one of the most important factors for predicting your ability to detect a significant signal change. If it is too low, noise in the images will dominate, and you will need to perform many more runs or subjects to achieve a desired statistical significance. For instance, if you are acquiring BOLD data on the same scanner with the exact same sequence, and with one set of parameters (e.g., voxel size, TR, etc.) you get intensities that are 100x greater than for another set of parameters, these two data sets will likely have very different SNRs (and probably tSNRs).
For more on these SNR relationships, you can check out papers from Christina Triantafyllou et al., e.g.,
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Dear all,
I used to do research in the field of wireless power transfer, where I usually tried to maximize the coupling between two magnetic resonators. Now I am doing work in RF-coil-design for MRI and inductive decoupling between adjacent coils in the array is essential.
I have been looking for some sources of explanation but I haven't been successful.
I might think that because of the coupling between adjacent coils, there might occur the frequency splitting effect. It will reduce the voltage at the resonance in each coil, which in turn reduces the SNR of the system.
Are there any more reasons why we need to use inductive decoupling?
Thanks
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Dr. Chu, Decoupling the coils in the array eliminates the splitting effect. This is easily seen by on a S12 or S22 measurement on a spectrum analyzer where reducing the overlap of two circular resonant RF coils to 11% of the coil area will reach a minimum and the spectral splitting will collapse.
This is described in the original NMR array coil paper by Roemer et. al - Magnetic Resonance in Medicine 16, 192-225 (1990). Since that paper additional methods that use capacitive and low-impedence pre-amps have been used to reduce coupling. The inductive and capacitive methods allow a high current to be run in the conductor to produce a strong RF magnetic field. The low-impedence amplifier technique reduces coil current to a very low value to reduce the coupling field. The first two techniques are strongly configuration dependent. The latter not as sensitive to orientation.
There is an extensive literature in this field. Much larger than can be listed here. I' m attaching the Roemer paper for your use.
Good luck in your research.
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I actually need a straight forward downloadable zip file of images. but whatever i found on google takes much process ( gives me contract pdf to sign and send them, dont know they even reply or not), Any Help ??
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I have YOLO-based algorithm dataset annotations for MRI brain dataset.
You can message me for more information. Refat Khan Pathan
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I have synthesized iron oxide naoparticles via co precipitation but after drying the powder nanoparticles were not attracted to magnet i want to use it for MR imaging so i need superparamagetic behavior. I don't know if my particles are superparamagnetic or not?
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One can try the hysteresis ( Magnetization (B-H) curve) experiment for knowing how long does the nanoparticle retains the magnetization.
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I am looking for DTI/MRI data from epileptic patients for a MSc thesis.
Regards
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Hi
We are working on the capability of MnO2 NPs for producing O2 inside cervix cells.
How can we measur the interacellular oxygen level? Which method would be best for it?
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There are different experimental procedures to investigate cellular Oxygen Concentration, like Microelectrodes, EPR (electron paramagnetic resonance), and optical methods.
For details go through the link
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I have structural MRI scans of 10 subjects. I am wondering if there is a way to find out which two subjects have the most similar MRI scans quantitatively.
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You can do sample cross-correlation, but for the fMRI data, you have to reshape the data matrix or write the function by yourself. MATLAB cross-correlation only covers one-dimensional data.
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I would like to do research on MRI images. Can you please suggest some websites from where MRI images can be downloaded. Thanking you. Gautam Talukdar. 
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I would like to find MRI images database for liver segmentation and classification.
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I'm interested in evaluting the evidence in the literature I've collected for spatial/anatomical variation in an MRI measure. The data consists of mean values, standard deviations and sample sizes, with widely varying numbers of data points for different regions.
They're not RCTs, but as per these answers:
and this package:
I've understood I can use the mean as an outcome measure, and can use the other data to calculate the sampling variances. My issue is I'm not sure of the best way to approach the widely different numbers/quality of studies for different regions. For example, I have estimates for overall grey matter or white matter from up to 30 studies, but for other regions I might have as few as one.
Broadly, I'm interested in two questions, that seem to me to imply different approaches:
1) To what extent does the existing literature support the idea that there IS regional variability? This would evaluate the evidence against the null hypothesis that there is no regional variability. I'd also like to evaluate the contribution of potential demographic and MRI-related confounders/ covariates, and if they prove to be significant, normalise the data with respect to them or otherwise account for them. This seems to imply a kind of regression across studies, but I'm not sure how best to account for the different contributions of different studies across regions.
2) What is the 'best' estimate (the most supported) of the value of my MRI measure in the literature. The object is partly to indicate the level of evidence for the 'best' estimate, in the hopes of encouraging better study of it in larger populations. I also want to compare the 'best extimate' to the values computed from a toy model informed by histology of what the value 'should' be. This seems to point to separate meta-analyses of each region, becuase the the level of evidence for each region is likely to be different.
I'm hoping for pointers as to the best method and approach to take. I'd thought to use R for the analysis, but if anyone has advice about other (preferably free) software that is suited to the task that would be useful too.
Many thanks
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Thanks a lot Babak Saravi, I've made headway with identifying methods and tools for my work but your comprehensive answer certainly adds some avenues to explore. Cheers, Ben
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Dear all,
I have 2 Bold runs of a resting state MRI of the same subject. I want to combine these two into a single bold run. I habe tried so far to use fslmerge by time, but it seems not to be the best way.
Do you know any better ways to do so?
I am doing further calculationa with correlations matrices of the rsfmri images.
best,
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It depends on how you are going to analyze the data. If you are going to use CONN Toolbox, you can easily define two sessions for each subject, then you don't need to merge the data.
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I am looking for a good/high-quality MRI dataset of the human pelvic region. Do you know where I can find this?
Thanks!
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If possible try to get from original MRI unit by downloading images of scans of MR Pelvis.
If you need if for any research or project purpose.
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i want to apply compression method on medical images from CT and MRI
how i can get this raw images ?
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Can you please suggest some websites where the MRI images can be downloaded for free.
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Hi. You can try this journal which is an Open Access Journal: Open Journal of Medical Imaging (https://www.scirp.org/journal/ojmi/)
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Hi all,
I am wondering about how to get a free dataset of MRI lumbar spine that contains lumbar disc herniation ?
Regards,
Yuwin
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I would suggest to collaborate with nearby hospital and get the MRI because later you have to mention it the research papers from where you have received the MRI and its details like slice thickness, Age, gender etc.
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