Implementation detail for paper "Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet"

Overview

Multi-level-colonoscopy-malignant-tissue-detection-with-adversarial-CAC-UNet Tweet

Implementation detail for our paper "Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet"

DigestPath 2019

The proposed scheme in this paper achieves the best results in MICCAI DigestPath2019 challenge (https://digestpath2019.grand-challenge.org/Home/) on colonoscopy tissue segmentation and classification task.

Dataset

Description of dataset can be found here: https://digestpath2019.grand-challenge.org/Dataset/

To download the the DigestPath2019 dataset, please sign the DATABASE USE AGREEMENT first at here: https://digestpath2019.grand-challenge.org/Download/

If you have problems about downing the dataset, please contact Prof. Hongsheng Li:[email protected]

Image sample:

Envs

  • Pytorch 1.0
  • Python 3+
  • cuda 9.0+

install

$ pip install -r  requirements.txt

apex : Tools for easy mixed precision and distributed training in Pytorch

$ git clone https://github.com/NVIDIA/apex
$ cd apex
$ pip install -v --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./

Dataset

├── data/
│   ├── tissue-train-neg/     
│   ├── tissue-train-pos-v1/

Preprocessing

$ cd code/
$ python preprocessing.py

Training

$ cd code/
$ python train.py --config_file='config/cac-unet-r50.yaml'

Citation

Please cite this paper in your publications if it helps your research:

@article{zhu2021multi,
  title={Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet},
  author={Zhu, Chuang and Mei, Ke and Peng, Ting and Luo, Yihao and Liu, Jun and Wang, Ying and Jin, Mulan},
  journal={Neurocomputing},
  volume={438},
  pages={165--183},
  year={2021},
  publisher={Elsevier}
}

About the multi-level adversarial segmentation part, you can read our ICASSP paper for more details:

@inproceedings{mei2020cross,
  title={Cross-stained segmentation from renal biopsy images using multi-level adversarial learning},
  author={Mei, Ke and Zhu, Chuang and Jiang, Lei and Liu, Jun and Qiao, Yuanyuan},
  booktitle={ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={1424--1428},
  year={2020},
  organization={IEEE}
}

Author

Ke Mei, Ting Peng, Chuang Zhu

If you have any questions, you can contact me directly.

Owner
CVSM Group - email: [email protected]
Codes of our papers are released in this GITHUB account.
CVSM Group - email: <a href=[email protected]">
The CLRS Algorithmic Reasoning Benchmark

Learning representations of algorithms is an emerging area of machine learning, seeking to bridge concepts from neural networks with classical algorithms.

DeepMind 251 Jan 05, 2023
Learning Chinese Character style with conditional GAN

zi2zi: Master Chinese Calligraphy with Conditional Adversarial Networks Introduction Learning eastern asian language typefaces with GAN. zi2zi(字到字, me

Yuchen Tian 2.2k Jan 02, 2023
[CVPR 2022] Back To Reality: Weak-supervised 3D Object Detection with Shape-guided Label Enhancement

Back To Reality: Weak-supervised 3D Object Detection with Shape-guided Label Enhancement Announcement 🔥 We have not tested the code yet. We will fini

Xiuwei Xu 7 Oct 30, 2022
"SOLQ: Segmenting Objects by Learning Queries", SOLQ is an end-to-end instance segmentation framework with Transformer.

SOLQ: Segmenting Objects by Learning Queries This repository is an official implementation of the paper SOLQ: Segmenting Objects by Learning Queries.

MEGVII Research 179 Jan 02, 2023
Bu repo SAHI uygulamasını mantığını öğreniyoruz.

SAHI-Learn: SAHI'den Beraber Kodlamak İster Misiniz Herkese merhabalar ben Kadir Nar. SAHI kütüphanesine gönüllü geliştiriciyim. Bu repo SAHI kütüphan

Kadir Nar 11 Aug 22, 2022
Tackling data scarcity in Speech Translation using zero-shot multilingual Machine Translation techniques

Tackling data scarcity in Speech Translation using zero-shot multilingual Machine Translation techniques This repository is derived from the NMTGMinor

Tu Anh Dinh 1 Sep 07, 2022
Speed-Test - You can check your intenet speed using this tool

Speed-Test Tool By Hez_X AVAILABLE ON : Termux & Kali linux & Ubuntu (Linux E

Hez-X 3 Feb 17, 2022
Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly

Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly Code for this paper Ultra-Data-Efficient GAN Tra

VITA 77 Oct 05, 2022
Train an RL agent to execute natural language instructions in a 3D Environment (PyTorch)

Gated-Attention Architectures for Task-Oriented Language Grounding This is a PyTorch implementation of the AAAI-18 paper: Gated-Attention Architecture

Devendra Chaplot 234 Nov 05, 2022
A PyTorch implementation of the Relational Graph Convolutional Network (RGCN).

Torch-RGCN Torch-RGCN is a PyTorch implementation of the RGCN, originally proposed by Schlichtkrull et al. in Modeling Relational Data with Graph Conv

Thiviyan Singam 66 Nov 30, 2022
Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners

Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners This repository is built upon BEiT, thanks very much! Now, we on

Zhiliang Peng 2.3k Jan 04, 2023
Repository for publicly available deep learning models developed in Rosetta community

trRosetta2 This package contains deep learning models and related scripts used by Baker group in CASP14. Installation Linux/Mac clone the package git

81 Dec 29, 2022
Implementation of "Selection via Proxy: Efficient Data Selection for Deep Learning" from ICLR 2020.

Selection via Proxy: Efficient Data Selection for Deep Learning This repository contains a refactored implementation of "Selection via Proxy: Efficien

Stanford Future Data Systems 70 Nov 16, 2022
A library built upon PyTorch for building embeddings on discrete event sequences using self-supervision

pytorch-lifestream a library built upon PyTorch for building embeddings on discrete event sequences using self-supervision. It can process terabyte-si

Dmitri Babaev 103 Dec 17, 2022
Pytorch implementation for the paper: Contrastive Learning for Cold-start Recommendation

Contrastive Learning for Cold-start Recommendation This is our Pytorch implementation for the paper: Yinwei Wei, Xiang Wang, Qi Li, Liqiang Nie, Yan L

45 Dec 13, 2022
PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems

PowerGridworld provides users with a lightweight, modular, and customizable framework for creating power-systems-focused, multi-agent Gym environments that readily integrate with existing training fr

National Renewable Energy Laboratory 37 Dec 17, 2022
Keras like implementation of Deep Learning architectures from scratch using numpy.

Mini-Keras Keras like implementation of Deep Learning architectures from scratch using numpy. How to contribute? The project contains implementations

MANU S PILLAI 5 Oct 10, 2021
Time-Optimal Planning for Quadrotor Waypoint Flight

Time-Optimal Planning for Quadrotor Waypoint Flight This is an example implementation of the paper "Time-Optimal Planning for Quadrotor Waypoint Fligh

Robotics and Perception Group 38 Dec 02, 2022
DAT4 - General Assembly's Data Science course in Washington, DC

DAT4 Course Repository Course materials for General Assembly's Data Science course in Washington, DC (12/15/14 - 3/16/15). Instructors: Sinan Ozdemir

Kevin Markham 779 Dec 25, 2022
Pneumonia Detection using machine learning - with PyTorch

Pneumonia Detection Pneumonia Detection using machine learning. Training was done in colab: DEMO: Result (Confusion Matrix): Data I uploaded my datase

Wilhelm Berghammer 12 Jul 07, 2022