How to train simple CNN model using data from COBRE dataset and get binary class (no_known_disorder and schizophrenia) predictions

[skhans]

I’ve downloaded the COBRE datasets (that contains control AND schizophrenia data only) from Schizoconnect. It is my first time to train model with .nii file. I am confused about how to make a model from .nii dataset. So, can anyone tell me the complete steps from extracting dataset file to predicting schizophrenia? That is, after extracting, I got 90 subjects (of no_known_disorder) and similarily for schizophrenia data, and in each subject there are multiple files, so which one I have to select for training model only .nii or others too?, How to make two folders so that one folder contains only .nii files of schizophrenia and second folder contains only no_known_disorder (i.e. healthy/control files of .nii), now how to preprocess data, how to read and open/display nii files using python script, then how to divide whole data into training and test set and then apply simple CNN model to get predictions that is, whether person is schizophrenic or not? Please help me to solve this issue using python script.

[JohannesWiesner]

Hi @skhans at least with regards to the multiple file issue, this might help:

What does echo suffix mean?

I am working with a sMRI dataset. In this dataset I got several files for each subject (different session dates and several runs per session). I only want to use the images from the first session and the first run of that session. In addition, for some subjects I got also several files with different echo suffixes (echo-01,echo-02). Does someone know what these suffixes mean? What’s the difference between echo-01 and echo-02 for instance? [image]

(Worked with the COBRE dataset a few years ago)