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
The method I am looking for should be non-invasive and within the scope of MRI modalities.
Which Thoracolumbar AO fracture subtype MRI would have the highest chance to change decision-making?
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
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!
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:
- 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!
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.
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.
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??
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?
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
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?
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.
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?
I need help please
I have executed these commands to read the MRI images with extension nii:
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?
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🖤
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 🙏
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.
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.
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
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!
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.
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 ?
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
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.
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.
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
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?
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?
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.
Gradient strength vs gradient amplitude. Is a 3T scanner with reduced gradient strength but higher amplitude as good?
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?
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)?
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,
Does anybody know a Matlab code for multiple sclerosis (MS) detection from MRI images using Convolutional Neural Networks (CNN)?
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.
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?
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.
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?
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,
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.
Or was the data collected is simply wrong
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?
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 ??
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?
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.
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.
I am wondering about how to get a free dataset of MRI lumbar spine that contains lumbar disc herniation ?