Skip to content

This repository contains the code of the AutoPCaSeg application, developed for the Bachelor Thesis. It is a deep learning-based software for the automatic segmentation of prostate cancer lesions.

License

Notifications You must be signed in to change notification settings

pilarnavarro/AutoPCaSeg

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

AutoPCaSeg

This repository contains the code of the AutoPCaSeg application, developed for my Bachelor Thesis. It is a deep learning-based software for automatic segmentation of prostate cancer lesions in T2-weighted MRI. It is structured as follows.

The utils folder contains all the necessary utilities:

  • preprocess.py -> contains all the necessary functions to preprocess the T2W images and their associated segmentation masks.

  • postproccess.py -> functions to postprocess the segmentation masks predicted by the models.

  • metrics.py -> implementation of the evaluation metrics

  • losses.py -> contains the utilities needed to compute the loss functions.

  • train.py -> includes all the functionality to train the models, evaluate them and make predictions on new data with them.

  • cross_val.py -> implementation of cross-validation used to evaluate the models.

  • save.py -> functions to save the results of the models.

The file run_cv.py executes 3-fold cross-validation with different parameters of the models and the training process, while the file run_test.py is intended to test the models on different test sets.

This software is written in Python 3.8.10 and has the following dependencies:

About

This repository contains the code of the AutoPCaSeg application, developed for the Bachelor Thesis. It is a deep learning-based software for the automatic segmentation of prostate cancer lesions.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages