Light

hubutui / gleason Goto Github PK

View Code? Open in Web Editor NEW

32.0 3.0 12.0 854 KB

My code using PSPNet for MICCAI Gleason Challenge 2019

Python 100.00%

gleason's Introduction

Update 20220118

This repo is archived since there is no updates, and I'm working on it anymore. For any question about the challenge, ask the organizers for help.

PSPNet for MICCAI Automatic Prostate Gleason Grading Challenge 2019

This is the code for MICCAI Automatic Prostate Gleason Grading Challenge 2019. Check here and here, we took the 1st place of task 1: pixel-level Gleason grade prediction and task 2: core-level Gleason score prediction (leaderboard).

Task 1 is regarded as a segmentation task, and we use PSPNet for this. And for task 2, we do not train a different network, but just produce the prediction from the prediction of task 1 according to the Gleason grading system.

The train script is based on reference script from torchvision 0.4.0 with minor modification. So, you need to install the latest PyTorch and torchvision >= 0.4.0. Check requirements.txt for all packages you need.

This repo use GluonCV-Torch, thanks for Hang Zhang's outstanding work!

Preprocessing

Each image is annotated in detail by several expert pathologists. So how to use this annotations is important. We use STAPLE to create final annotations used in training. Check the preprocessing.py script for detail.

Training

To run the training, simply run python train.py, check python train_gleason.py --help for available args.

Inference

To run the inference, simply run python inference.py, check python inference.py --help for available args.

Note

I don't quite understand task2, and got it wrong when I participated this challenge. I would sincerely advise you read this paper, which is written by the organizers and submitted to JBHI, for more detail about this challenge. I would not update any codes in this repository anymore.

gleason's People

Contributors

Stargazers

Watchers

Forkers

jagdeeshgughalot maggiepas amazingftt phuongchi911 jovenwayfarer samuelschen winnie-lings dengjiongshen deepmd-production deepmd-cancer wangwangwang978

gleason's Issues

About the challenge

Hi,
I just found this repo! I was also a participant in the challenge. After the challenge the organizers said they were going to publish a paper. Do you know what happened to that? I tried to contact them but got no answer.

Question about the maskdir/Gleason.py file

Inference?

Hello, thank you for publishing the code. Can you upload your inference.py?

Question about the preprecessing

When I run the 'preprocess.py', I got a new class 7 which is not in 0 - 6. Is this correct or not? Thanks. Moreover, how long and how many GPU you use to train the PSPNet？ Could you please share the trained model for inference? Thanks again.

Question for learning rate

Hi, hubutui.

I'm Dong Un Kang.

I am interested in prostate cancer segmentation. so, I'm trying to replicate your code.

I have a question for running code method.

Did you set learning rate as 0.01 for training?

Sincerely, thank you for your providing code.

Question about the training data and validation data

I encounter the following problems when try to reimplement you rexperiment:

For the validation data which contains 44 images, how do you choose them? Are you randomly select them from all 244 images?
When training the PSPNet, you initialize it with pretrained model on ADE dataset or not?
What's the best mean IoU of your final model when you do validation and how do you solve the problem of unbalanced training samples?
Why train the PSPNet with 6 classes (0 - 5) rather than 4 classes (benign, maglinant(3, 4, 5)) since in the test procedure only exist 4 classes?

benign versus cancerous classification

Hi

How can I do benign versus cancerous (Gleason grades 3, 4, and 5) classification,

as well as ow-grade (Gleason grade 3) versus high-grade (Gleason
grades 4 and 5). I mean how can I generate data for each class?

Thanks

The paper or report about model.

Where I can find the report or paper about this model?My wechat is szj_lucky0904,hopely receive your reply! Thanks!

Unable to use gluoncvth

After installing gluoncvth(0.0.0), then I run train.py, an error occured, AttributeError: module 'gluoncvth' has no attribute 'models', Can anyone tell me how to fix this? Thanks in advance.

Recommend Projects

React

A declarative, efficient, and flexible JavaScript library for building user interfaces.
Vue.js

🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
Typescript

TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
TensorFlow

An Open Source Machine Learning Framework for Everyone
Django

The Web framework for perfectionists with deadlines.
Laravel

A PHP framework for web artisans
D3

Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

javascript

JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
web

Some thing interesting about web. New door for the world.
server

A server is a program made to process requests and deliver data to clients.
Machine learning

Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Visualization

Some thing interesting about visualization, use data art
Game

Some thing interesting about game, make everyone happy.

Recommend Org

Facebook

We are working to build community through open source technology. NB: members must have two-factor auth.
Microsoft

Open source projects and samples from Microsoft.
Google

Google ❤️ Open Source for everyone.
Alibaba

Alibaba Open Source for everyone
D3

Data-Driven Documents codes.
Tencent

China tencent open source team.