/Cardiac-MRI-Segmentation

Primary LanguagePython

Cardiac-MRI-Segmentation

Project Description

This is my graduation project. Based on 3D-Unet, a 3D-segmentation network is implemented.

Project Architecture

MRI_data_read.py

  • test code for data read

dataset.py

  • dataloader for pytorch

dataset_generator.py

  • generate data for training and validation from raw medical images

loss_function.py

  • implementation of loss function used in training

main_rev.py

  • contains some core function, train and predict

metrics.py

  • implementaion of metrics
  • it is slow, may need to optimize.

models.py

  • implementation of network model in pytorch

utli.py

  • some auxiliary function

test.py

  • implement a complete test program using the network
  • now finished.

timeTick.py

  • implement a decorator for time tick.

transform3d.py

  • implement class for transforms.
  • composed of tranforms is supported.
  • random select from transforms is supported.

Current Work

  • now working on 3D unet training.

To Do

  • implement model_zoo.py for different models.
  • optimize metrics.py speed.
  • transform3d.py for data augumation, enrich methods.
  • fix bug in test.py dynamicly select num_classes.
  • in np cutter, if stride is too large, may generate minus value in position.
  • add remap() in util.py remap [0,1,..7] to origin label value to visualize better.

Further plans

  • multi-resolution enhancement
  • multi-model enhancement