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
Augmented CLIP - Training simple models to predict CLIP image embeddings from text embeddings, and vice versa.

Train aug_clip against laion400m-embeddings found here: https://laion.ai/laion-400-open-dataset/ - note that this used the base ViT-B/32 CLIP model. S

Peter Baylies 55 Sep 13, 2022
BEGAN in PyTorch

BEGAN in PyTorch This project is still in progress. If you are looking for the working code, use BEGAN-tensorflow. Requirements Python 2.7 Pillow tqdm

Taehoon Kim 260 Dec 07, 2022
UIUCTF 2021 Public Challenge Repository

UIUCTF-2021-Public UIUCTF 2021 Public Challenge Repository Notes: every challenge folder contains a challenge.yml file in the format for ctfcli, CTFd'

SIGPwny 15 Nov 03, 2022
Unofficial implementation of One-Shot Free-View Neural Talking Head Synthesis

face-vid2vid Usage Dataset Preparation cd datasets wget https://yt-dl.org/downloads/latest/youtube-dl -O youtube-dl chmod a+rx youtube-dl python load_

worstcoder 68 Dec 30, 2022
Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks

Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks Contributions A novel pairwise feature LSP to extract structural

31 Dec 06, 2022
IDM: An Intermediate Domain Module for Domain Adaptive Person Re-ID,

Intermediate Domain Module (IDM) This repository is the official implementation for IDM: An Intermediate Domain Module for Domain Adaptive Person Re-I

Yongxing Dai 87 Nov 22, 2022
Segmentation in Style: Unsupervised Semantic Image Segmentation with Stylegan and CLIP

Segmentation in Style: Unsupervised Semantic Image Segmentation with Stylegan and CLIP Abstract: We introduce a method that allows to automatically se

Daniil Pakhomov 134 Dec 19, 2022
Principled Detection of Out-of-Distribution Examples in Neural Networks

ODIN: Out-of-Distribution Detector for Neural Networks This is a PyTorch implementation for detecting out-of-distribution examples in neural networks.

189 Nov 29, 2022
PyTorch code to run synthetic experiments.

Code repository for Invariant Risk Minimization Source code for the paper: @article{InvariantRiskMinimization, title={Invariant Risk Minimization}

Facebook Research 345 Dec 12, 2022
Official implementation of "Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets" (CVPR2021)

Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets This is the official implementation of "Towards Good Pract

Sanja Fidler's Lab 52 Nov 22, 2022
Source code for PairNorm (ICLR 2020)

PairNorm Official pytorch source code for PairNorm paper (ICLR 2020) This code requires pytorch_geometric=1.3.2 usage For SGC, we use original PairNo

62 Dec 08, 2022
Aerial Single-View Depth Completion with Image-Guided Uncertainty Estimation (RA-L/ICRA 2020)

Aerial Depth Completion This work is described in the letter "Aerial Single-View Depth Completion with Image-Guided Uncertainty Estimation", by Lucas

ETHZ V4RL 70 Dec 22, 2022
K-Means Clustering and Hierarchical Clustering Unsupervised Learning Solution in Python3.

Unsupervised Learning - K-Means Clustering and Hierarchical Clustering - The Heritage Foundation's Economic Freedom Index Analysis 2019 - By David Sal

David Salako 1 Jan 12, 2022
PyTorch implementation of "VRT: A Video Restoration Transformer"

VRT: A Video Restoration Transformer Jingyun Liang, Jiezhang Cao, Yuchen Fan, Kai Zhang, Rakesh Ranjan, Yawei Li, Radu Timofte, Luc Van Gool Computer

Jingyun Liang 837 Jan 09, 2023
Fair Recommendation in Two-Sided Platforms

Fair Recommendation in Two-Sided Platforms

gourabgggg 1 Nov 10, 2021
Script for getting information in discord

User-info.py Script for getting information in https://discord.com/ Instalação: apt-get update -y apt-get upgrade -y apt-get install git pkg install

Moleey 1 Dec 18, 2021
CountDown to New Year and shoot fireworks

CountDown and Shoot Fireworks About App This is an small application make you re

5 Dec 31, 2022
A implemetation of the LRCN in mxnet

A implemetation of the LRCN in mxnet ##Abstract LRCN is a combination of CNN and RNN ##Installation Download UCF101 dataset ./avi2jpg.sh to split the

44 Aug 25, 2022
[NeurIPS 2021] Low-Rank Subspaces in GANs

Low-Rank Subspaces in GANs Figure: Image editing results using LowRankGAN on StyleGAN2 (first three columns) and BigGAN (last column). Low-Rank Subspa

112 Dec 28, 2022
Code for "Retrieving Black-box Optimal Images from External Databases" (WSDM 2022)

Retrieving Black-box Optimal Images from External Databases (WSDM 2022) We propose how a user retreives an optimal image from external databases of we

joisino 5 Apr 13, 2022