1st-in-MICCAI2020-CPM - Combined Radiology and Pathology Classification

Overview

Combined Radiology and Pathology Classification

MICCAI 2020 Combined Radiology and Pathology Classification Challenge (1st place solution)

Hardware

  • 4*NVIDIA Tesla P40 GPU cards
  • 32GB of RAM

Pre-requisites:

  • torch >=1.3.0, nibabel, batchgenerators

Usage

Preparation

  1. Data Preparation
  • Download challenge data
  1. Training Splits (spilt/train1.txt)

MRI training

  1. Trainning Glioblastoma/None Glioblastoma(pretrain 3d medical Weights )
cd mri
python train_g.py

RESNET=False  #False is resnet, True is densenet
model.conv1 = nn.Conv3d(4,....)  #The input channel is 5 if the tumor segmentation region exists, otherwise it is 4



model = densenet.densenet121(first=5,..)  #The input channel is 5 if the tumor segmentation region exists, otherwise it is 4 
#datasets.brain.py
BrainDataset_AO,BrainDataset_G # AO dataset,G_dataset  
return img_array[:4], labels #The input channel is 5 if the tumor segmentation region exists, otherwise it is 4

2.Trainning Oligodendroglioma/Lower grade astrocytoma After the first stage of training, the second stage of training needs to use the weights trained in the first stage to warm up

cd mri
python train_ao.py

WSI training

Reference This is code based on MedicalNet

Citation

Please use below to cite this paper if you find our work useful in your research.

💡 Type hints for Numpy

Type hints with dynamic checks for Numpy! (❒) Installation pip install nptyping (❒) Usage (❒) NDArray nptyping.NDArray lets you define the shape and

Ramon Hagenaars 377 Dec 28, 2022
A PyTorch implementation of QANet.

QANet-pytorch NOTICE I'm very busy these months. I'll return to this repo in about 10 days. Introduction An implementation of QANet with PyTorch. Any

H. Z. 343 Nov 03, 2022
TensorFlow implementation of "Attention is all you need (Transformer)"

[TensorFlow 2] Attention is all you need (Transformer) TensorFlow implementation of "Attention is all you need (Transformer)" Dataset The MNIST datase

YeongHyeon Park 4 Jan 05, 2022
NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go

NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go This repository provides our implementation of the CVPR 2021 paper NeuroMorp

Meta Research 35 Dec 08, 2022
Face Alignment using python

Face Alignment Face Alignment using python Input Image Aligned Face Aligned Face Aligned Face Input Image Aligned Face Input Image Aligned Face Instal

Sajjad Aemmi 28 Nov 23, 2022
Wider or Deeper: Revisiting the ResNet Model for Visual Recognition

ademxapp Visual applications by the University of Adelaide In designing our Model A, we did not over-optimize its structure for efficiency unless it w

Zifeng Wu 338 Dec 12, 2022
SMD-Nets: Stereo Mixture Density Networks

SMD-Nets: Stereo Mixture Density Networks This repository contains a Pytorch implementation of "SMD-Nets: Stereo Mixture Density Networks" (CVPR 2021)

Fabio Tosi 115 Dec 26, 2022
.NET bindings for the Pytorch engine

TorchSharp TorchSharp is a .NET library that provides access to the library that powers PyTorch. It is a work in progress, but already provides a .NET

Matteo Interlandi 17 Aug 30, 2021
Torchlight2 lan game server tool - A message forwarding tool for Torchlight 2 lan game

Torchlight 2 Lan Game Server Tool A message forwarding tool for Torchlight 2 lan

Huaijun Jiang 3 Nov 01, 2022
An official source code for "Augmentation-Free Self-Supervised Learning on Graphs"

Augmentation-Free Self-Supervised Learning on Graphs An official source code for Augmentation-Free Self-Supervised Learning on Graphs paper, accepted

Namkyeong Lee 59 Dec 01, 2022
data/code repository of "C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer"

C2F-FWN data/code repository of "C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer" (https://arxiv.org/abs/

EKILI 46 Dec 14, 2022
A Streamlit component to render ECharts.

Streamlit - ECharts A Streamlit component to display ECharts. Install pip install streamlit-echarts Usage This library provides 2 functions to display

Fanilo Andrianasolo 290 Dec 30, 2022
Dynamic hair modeling from monocular videos using deep neural networks

Dynamic Hair Modeling The source code of the networks for our paper "Dynamic hair modeling from monocular videos using deep neural networks" (SIGGRAPH

53 Oct 18, 2022
PyTorch implementation of Lip to Speech Synthesis with Visual Context Attentional GAN (NeurIPS2021)

Lip to Speech Synthesis with Visual Context Attentional GAN This repository contains the PyTorch implementation of the following paper: Lip to Speech

6 Nov 02, 2022
Pytorch Implementation of Adversarial Deep Network Embedding for Cross-Network Node Classification

Pytorch Implementation of Adversarial Deep Network Embedding for Cross-Network Node Classification (ACDNE) This is a pytorch implementation of the Adv

陈志豪 8 Oct 13, 2022
Continuous Time LiDAR odometry

CT-ICP: Elastic SLAM for LiDAR sensors This repository implements the SLAM CT-ICP (see our article), a lightweight, precise and versatile pure LiDAR o

385 Dec 29, 2022
An example of semantic segmentation using tensorflow in eager execution.

Semantic segmentation using Tensorflow eager execution Requirement Python 2.7+ Tensorflow-gpu OpenCv H5py Scikit-learn Numpy Imgaug Train with eager e

Iñigo Alonso Ruiz 25 Sep 29, 2022
SMIS - Semantically Multi-modal Image Synthesis(CVPR 2020)

Semantically Multi-modal Image Synthesis Project page / Paper / Demo Semantically Multi-modal Image Synthesis(CVPR2020). Zhen Zhu, Zhiliang Xu, Anshen

316 Dec 01, 2022
[AAAI 2022] Separate Contrastive Learning for Organs-at-Risk and Gross-Tumor-Volume Segmentation with Limited Annotation

A paper Introduction This is an official release of the paper Separate Contrastive Learning for Organs-at-Risk and Gross-Tumor-Volume Segmentation wit

Jiacheng Wang 14 Dec 08, 2022
Code for the tech report Toward Training at ImageNet Scale with Differential Privacy

Differentially private Imagenet training Code for the tech report Toward Training at ImageNet Scale with Differential Privacy by Alexey Kurakin, Steve

Google Research 29 Nov 03, 2022