I'm wondering if anyone know so of a good python tool for skull stripping and brain segmentation? Basically something like freesurfer, but can work totally within a jupyter notebook. Looking through the FSLPY documentation it doesn't seem to have this capability included in it's python tools.

Edit: Realized it's under "BET" in FSLPY: https://open.win.ox.ac.uk/pages/fsl/fslpy/fsl.wrappers.bet.html#module-fsl.wrappers.bet

I have a question about the specialists who read the images from patients scans, do they look at all and everything on the scan or just whatever the patient states is symptomatic and only check those areas for concern? Hope the make sense.

Hi all I'm new to this group and am looking for the right place to ask this question.

I'm in a class learning python and neuroimaging analysis and have been having trouble with the templateflow atlases. There doesn't seem to be a simple straightforward guide to the atlases available, definitions, etc

To start, how do people navigate slicing orientation? I tried calling hocpa and pulling orientation metrics, but 1) they are not easily legible, and 2) I believe they are changed once I call imshow().

The output for orientation in .affline is a matrix:

[[ 1. 0. -0. -96.]
[ 0. 1. -0. -132.]
[ 0. 0. 1. -78.]
[ 0. 0. 0. 1.]]

The output for nib.aff2axcodes(atlas_img.affine) is ('R', 'A', 'S')

Thanks for any guidance you may have. If you think there's a better place somewhere to ask, please lmk!

Hi everyone,

I am very new to neuroimaging and am currently involved in a project analyzing RS-fMRI data via ICA.

As I write the analysis plan, one of my collaborators wants me to detail things like the normality of data, outliers, homoscedasticity, etc. In other words, check for the assumptions you learn in statistics class. Of note, this person has zero experience with imaging.

I'm still so new to this, but in my limited experience, I have never seen RS-fMRI studies attempt to answer these questions, at least not how she outlines them. Instead, I have always seen that as the role of a preprocessing pipeline: preparing the data for proper statistical analysis. I imagine there is some overlap in the standard preprocessing pipelines and the questions she is asking me, but I need to learn more first to know for certain.

I just want to ask: am I missing something here? Is there more "assumptions" or preliminary analyses I need to be running before "standard" preprocessing pipelines to ensure my data is suitable for analysis?

Thank you,

I’m curious to hear from anyone working in this field. If I’d like to get involved in neuroimaging research with a focus on data acquisition and analysis, would a background in statistics, computer science, or a combination of both be enough? Or I need a degree in electrical/computer engineering? I’d greatly appreciate your insights!

Hi,

I was hoping to get some help. I am working in DSI studio and wanted to import regions from the Chakravarty atlas for my analysis. I know it's in LeadDBS but I am having issues 1) getting LeadDBS to run without quitting out 2) exporting the atlas in Nifti format from Lead DBS.

Would anyone be able to help me? Am I thinking about this the wrong way?

Thanks!

Hello all,

I have the MRI functional connectivity gradients data of two groups. Connectivity matrices and gradients are calculated based on Schaefer atlas (7 networks, 400 regions). I want to compare these gradient values between the two groups in SPSS. I want to take the repeated measures nature of the data into consideration, and make necessary corrections, but I cannot decide which statistical test I should use.

Would it be wrong if I conduct 7 separate two-way mixed ANOVAs for each network and make pairwise comparisons using Bonferroni correction? For example the visual network consists of 61 regions in the Schaefer atlas, so my analysis would be 2x61 mixed ANOVA (visual network regions as the within variable, group as the between variable).

If this is wrong, which method should I follow?

I appreciate any help and guidance, thank you in advance!

I’m a layperson doing some personal analysis of brain region sizes and proportions, and I’m trying to understand more about what is considered normal.

I understand that there are no unified datasets, but I just want to see if there is any severe deviation in my brain's volumetry obtained from FreeSurfer.

• What are the typical sizes of the following (refer attached image) brain regions in healthy adults?
• What are the typical proportions of these regions relative to each other and to the overall brain volume?
• How much asymmetry between corresponding regions (like left vs. right) is considered normal?

For example, I see that my left hemisphere's superior temporal volume is 30% larger than the right hemisphere's. 9570 mm3 vs 7381 mm3. I don't know if this is a huge deviation or not.

https://preview.redd.it/pib9qzyl4lpd1.jpg?width=682&format=pjpg&auto=webp&s=118ccee6eb2bebf6011576737e9986b6c86e52a9

I posted something similar about 7 months ago, but I’m all the excitement I completely ignored the fact that it will be hella difficult to couple pupil changes to increased hemoglobin activity in The ACC given the delayed response.

Are there any techniques used to correlate pupil responses to hemoglobin changes available?

Hi everyone,

What’s the most efficient way to convert DICOM to BIDS? I’m new to neuroimaging (and research in general), so I’d prefer the simplest tool to use.

Thanks in advance!

I have volumetric stats from Freesurfer. I want to compare the volumes of different regions of my brain with that of healthy controls. I see multiple datasets from different entities with 50, 60, 70, etc. healthy controls.

Is there any unified dataset where I can get the list of average volumes of brain regions in a healthy control subject of my age and gender?

I do not have any formal medical training. I want to do volumetric analysis of my MRI data. The open source tools and AI models are too complex for me. Where can I get this done online? Are there freelancing radiologists?

Hello. Im doing a Research paper on using Neural networks to scan and diagnose individuals with ASD. I understand the processing steps of the data completely fine but the description of the neural networks architecture is a little confusing and vague and the author hasn’t responded to my source code request. I’m also a little lost on this they fuse the data. If anyone has some good insight let me know. This is my white whale so I’m gonna be working on this for a while.

How to normalize GM/WM/subcortical structure volume in freesurfer, dividing by eTIV or something else?

Hi I am new to signal processing and psychology. I am a masters student working on fnirs and had some doubts in signal processing. I am using https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2013.00935/full this dataset. In the mentioned paper they used a low pass filter with cutoff of 0.5 and used a moving average filter. So what confuses me is how to come up with a threshold freq or even know that the signal now has no disturbances.

Hello r/neuroimaging community,

I'm currently working on a project using Nilearn, specifically the BASC122 parcellation, to plot brain images. I've run into a bit of a challenge when it comes to assigning and matching the parcellation to anatomical names.

So far, my approach has been to approximate the regions by using the Harvard-Oxford atlas. I calculate the Euclidean distance between the X, Y, Z coordinates of the parcellations and the corresponding Harvard-Oxford anatomical labels. However, this method is quite rough and regions matched are way off than where they should be in visualizations, and I’m concerned it might not be the most accurate, especially when dealing with overlaps and finer details.

Ideally, I'd like to find a way to more precisely match each parcellation in BASC122 to a specific anatomical region name, taking overlaps into account. Has anyone dealt with a similar issue, or can anyone suggest a more effective method or tool for this task?

Thanks in advance for any advice or guidance!

Hi y'all, I am planning on joining a lab working on neuroimaging this Fall and I am super excited to get started in this field. However, I have never worked in this field ever before and I am interested in diving into the machine learning and computational tool development side of it, working on generating clinical insights and diagnostic tools. I would love to know if there are some resources I could get started with and would love to connect with folks in this space to explore it further. Thanks!