RSNA Intracranial Hemorrhage Detection with python

Related tags

Deep LearningIntracranial-Hemorrhage-Detection
Overview

RSNA Intracranial Hemorrhage Detection

This is the source code for the first place solution to the RSNA2019 Intracranial Hemorrhage Detection Challenge.

Solution write up: Link.

Solutuoin Overview

image

Dependencies

  • opencv-python==3.4.2
  • scikit-image==0.14.0
  • scikit-learn==0.19.1
  • scipy==1.1.0
  • torch==1.1.0
  • torchvision==0.2.1

CODE

  • 2DNet
  • 3DNet
  • SequenceModel

2D CNN Classifier

Pretrained models

Preprocessing

image

Prepare csv file:

download data.zip: https://drive.google.com/open?id=1buISR_b3HQDU4KeNc_DmvKTYJ1gvj5-3

  1. convert dcm to png
python3 prepare_data.py -dcm_path stage_1_train_images -png_path train_png
python3 prepare_data.py -dcm_path stage_1_test_images -png_path train_png
python3 prepare_data.py -dcm_path stage_2_test_images -png_path test_png
  1. train
python3 train_model.py -backbone DenseNet121_change_avg -img_size 256 -tbs 256 -vbs 128 -save_path DenseNet121_change_avg_256
python3 train_model.py -backbone DenseNet169_change_avg -img_size 256 -tbs 256 -vbs 128 -save_path DenseNet169_change_avg_256
python3 train_model.py -backbone se_resnext101_32x4d -img_size 256 -tbs 80 -vbs 40 -save_path se_resnext101_32x4d_256
  1. predict
python3 predict.py -backbone DenseNet121_change_avg -img_size 256 -tbs 4 -vbs 4 -spth DenseNet121_change_avg_256
python3 predict.py -backbone DenseNet169_change_avg -img_size 256 -tbs 4 -vbs 4 -spth DenseNet169_change_avg_256
python3 predict.py -backbone se_resnext101_32x4d -img_size 256 -tbs 4 -vbs 4 -spth se_resnext101_32x4d_256

After single models training, the oof files will be saved in ./SingleModelOutput(three folders for three pipelines).

After training the sequence model, the final submission will be ./FinalSubmission/final_version/submission_tta.csv

Sequence Models

Sequence Model 1

image

Sequence Model 2

image

Path Setup

Set data path in ./setting.py

download

download [csv.zip]

download [feature samples]

Sequence Model Training

CUDA_VISIBLE_DEVICES=0 python main.py

The final submissions are in the folder ../FinalSubmission/version2/submission_tta.csv

Final Submission

Private Leaderboard:

  • 0.04383

Reference

If you find our work useful in your research or if you use parts of this code please consider citing our paper:

  title={A deep learning algorithm for automatic detection and classification of acute intracranial hemorrhages in head CT scans},
  author={Wang, Xiyue and Shen, Tao and Yang, Sen and Lan, Jun and Xu, Yanming and Wang, Minghui and Zhang, Jing and Han, Xiao},
  journal={NeuroImage: Clinical},
  volume={32},
  pages={102785},
  year={2021},
  publisher={Elsevier}
}

TODO

  • Pre-trained models
  • 2DCNN + SeqModel end-to-end training
  • 3DCNN training
Owner
GitHub Repository
Official PyTorch code for Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution (MANet, ICCV2021)

Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution (MANet, ICCV2021) This repository is the official PyTorc

Jingyun Liang 139 Dec 29, 2022
Anomaly detection related books, papers, videos, and toolboxes

Anomaly Detection Learning Resources Outlier Detection (also known as Anomaly Detection) is an exciting yet challenging field, which aims to identify

Yue Zhao 6.7k Dec 31, 2022
Network Compression via Central Filter

Network Compression via Central Filter Environments The code has been tested in the following environments: Python 3.8 PyTorch 1.8.1 cuda 10.2 torchsu

2 May 12, 2022
Very Deep Convolutional Networks for Large-Scale Image Recognition

pytorch-vgg Some scripts to convert the VGG-16 and VGG-19 models [1] from Caffe to PyTorch. The converted models can be used with the PyTorch model zo

Justin Johnson 217 Dec 05, 2022
An implementation of the [Hierarchical (Sig-Wasserstein) GAN] algorithm for large dimensional Time Series Generation

Hierarchical GAN for large dimensional financial market data Implementation This repository is an implementation of the [Hierarchical (Sig-Wasserstein

11 Nov 29, 2022
Tensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution

Single Image Super-Resolution with EDSR, WDSR and SRGAN A Tensorflow 2.x based implementation of Enhanced Deep Residual Networks for Single Image Supe

Martin Krasser 1.3k Jan 06, 2023
Pytorch implementation of

EfficientTTS Unofficial Pytorch implementation of "EfficientTTS: An Efficient and High-Quality Text-to-Speech Architecture"(arXiv). Disclaimer: Somebo

Liu Songxiang 109 Nov 16, 2022
A TensorFlow implementation of the Mnemonic Descent Method.

MDM A Tensorflow implementation of the Mnemonic Descent Method. Mnemonic Descent Method: A recurrent process applied for end-to-end face alignment G.

123 Oct 07, 2022
Unofficial implementation of HiFi-GAN+ from the paper "Bandwidth Extension is All You Need" by Su, et al.

HiFi-GAN+ This project is an unoffical implementation of the HiFi-GAN+ model for audio bandwidth extension, from the paper Bandwidth Extension is All

Brent M. Spell 134 Dec 30, 2022
What can linearized neural networks actually say about generalization?

What can linearized neural networks actually say about generalization? This is the source code to reproduce the experiments of the NeurIPS 2021 paper

gortizji 11 Dec 09, 2022
3D Generative Adversarial Network

Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling This repository contains pre-trained models and sampling

Chengkai Zhang 791 Dec 20, 2022
SimBERT升级版（SimBERTv2）！

RoFormer-Sim RoFormer-Sim，又称SimBERTv2，是我们之前发布的SimBERT模型的升级版。 介绍 https://kexue.fm/archives/8454 训练 tensorflow 1.14 + keras 2.3.1 + bert4keras 0.10.6 下载

318 Dec 31, 2022
Powerful unsupervised domain adaptation method for dense retrieval.

Powerful unsupervised domain adaptation method for dense retrieval

Ubiquitous Knowledge Processing Lab 191 Dec 28, 2022
UFPR-ADMR-v2 Dataset

UFPR-ADMR-v2 Dataset The UFPR-ADMRv2 dataset contains 5,000 dial meter images obtained on-site by employees of the Energy Company of Paraná (Copel), w

Gabriel Salomon 8 Sep 29, 2022
[AI6122] Text Data Management & Processing

[AI6122] Text Data Management & Processing is an elective course of MSAI, SCSE, NTU, Singapore. The repository corresponds to the AI6122 of Semester 1, AY2021-2022, starting from 08/2021. The instruc

HT. Li 1 Jan 17, 2022
Code for CVPR2021 "Visualizing Adapted Knowledge in Domain Transfer". Visualization for domain adaptation. #explainable-ai

Visualizing Adapted Knowledge in Domain Transfer @inproceedings{hou2021visualizing, title={Visualizing Adapted Knowledge in Domain Transfer}, auth

Yunzhong Hou 80 Dec 25, 2022
🏖 Keras Implementation of Painting outside the box

Keras implementation of Image OutPainting This is an implementation of Painting Outside the Box: Image Outpainting paper from Standford University. So

Bendang 1.1k Dec 10, 2022
Video Autoencoder: self-supervised disentanglement of 3D structure and motion

Video Autoencoder: self-supervised disentanglement of 3D structure and motion This repository contains the code (in PyTorch) for the model introduced

157 Dec 22, 2022
Character-Input - Create a program that asks the user to enter their name and their age

Character-Input Create a program that asks the user to enter their name and thei

PyLaboratory 0 Feb 06, 2022
Independent and minimal implementations of some reinforcement learning algorithms using PyTorch (including PPO, A3C, A2C, ...).

PyTorch RL Minimal Implementations There are implementations of some reinforcement learning algorithms, whose characteristics are as follow: Less pack

Gemini Light 4 Dec 31, 2022