nibabel | Python package to access a cacophony of neuro-imaging file

I am new to deep learning, currently working on an image segmentation network. I managed to train the network, but the problem is to translate the network response into nii format. I cut the training sample from the CT images into 512X512 slices, and then slices into 128X128 patches. Accordingly, I transfer the patches to the input of the network and get the mask 128x128 at the output. I managed to group the masks into a numpy array. But when transferring from an array to nii and trying to impose the resulting mask on the original CT, my scales do not match. Please, tell me what could be the problem? I really appreciate any help.

For example and simplicity, I took a mask from the training sample.

I want to train a model with a custom generator class but model.fit() gives me this error:

I'm trying to perform some MRI segmentation using a deep learning model, but I'm getting a error related to the dimension of the image, not sure why.

For getting the list of installed libraries, I run the following command in Jupyter Notebook:

I have a binary 3d array that has small groups of 1 and large groups of 1. I want to search the array and when a 1 is found I want to search the surrounding values in the x,y,z directions and count how many 1 are connected. If there are less than x amount of 1 I want to set that group to 0. The entire 3d array consists of 1 and 0.

Array Example:

I have used python to analyse some fMRI data and would now like to save my results as niftis that I can then use in an SPM analysis.

My data scores is an array of float64 of shape (97, 115, 97). I have used the following code to save it:

I’m still approaching programming in python. For the first time i'm trying working with histograms and fit!

In particular, i have a dataset and i made a histogram of it. At this point i should do a rayleigh fit but i can't figure out the correct way to set the parameters correctly. I read that loc and scale, which should be the parameters of fit are usually set as 0 and 1. Obviously, in this way, the fit doesn’t work well!!! Is there someone who can help me? To be clear I'am attaching the code I am using.

Thank you.

I am trying to take a number of DICOM stacks and convert them to Nifti files. When I do the conversion and open the new Nifti file in a 3D viewer the volume is smashed together in the z direction. The Nifti files do not know what the spacing is between slices. To my understanding imageio.volread() does not read the metadata. I tried using pydicom.filereader.dcmread() but that only reads one file. How can I copy the metadata from the DICOM stack to the Nifti file when converting formats?

Is it possible to take a 3D array and and turn it into a coordinate system? My array consists of 0s and 1s. If the value is 1 I want to take the xyz coordinate. In the end I want to output all coordinates to a csv file.