RSNA Intracranial Hemorrhage Detection with python

Last update: Nov 30, 2022

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

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

seresnext101_256*256 [seresnext101]
densenet169_256*256 [densenet169]
densenet121_512*512 [densenet121]

Preprocessing

Prepare csv file:

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

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

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

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

Sequence Model 2

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

Example scripts for the detection of lanes using the ultra fast lane detection model in ONNX.

35 Sep 7, 2022

Example scripts for the detection of lanes using the ultra fast lane detection model in Tensorflow Lite.

TFlite Ultra Fast Lane Detection Inference Example scripts for the detection of lanes using the ultra fast lane detection model in Tensorflow Lite. So

12 Aug 27, 2022

This project deals with the detection of skin lesions within the ISICs dataset using YOLOv3 Object Detection with Darknet.

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Skin Lesion detection using YOLO This project deal

1 Nov 22, 2021

Implementation of the state of the art beat-detection, downbeat-detection and tempo-estimation model

The ISMIR 2020 Beat Detection, Downbeat Detection and Tempo Estimation Model Implementation. This is an implementation in TensorFlow to implement the

1 Nov 12, 2021

This is a GUI interface which can process forest fire detection, smoke detection and fire segmentation

This is a GUI interface which can process forest fire detection, smoke detection and fire segmentation. Yolov5 is used to detect fire and smoke and unet is used to segment fire.

7 Jan 8, 2023

Cancer-and-Tumor-Detection-Using-Inception-model - In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks, specifically here the Inception model by google.

Cancer-and-Tumor-Detection-Using-Inception-model In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks

1 Jan 1, 2022

Hybrid CenterNet - Hybrid-supervised object detection / Weakly semi-supervised object detection

RSNA Intracranial Hemorrhage Detection with python

Related tags

Overview

RSNA Intracranial Hemorrhage Detection

Solutuoin Overview

Dependencies

CODE

2D CNN Classifier

Pretrained models

Preprocessing

Sequence Models

Sequence Model 1

Sequence Model 2

Path Setup

download

Sequence Model Training

Final Submission

Private Leaderboard:

Reference

TODO

You might also like...

Example scripts for the detection of lanes using the ultra fast lane detection model in ONNX.

Example scripts for the detection of lanes using the ultra fast lane detection model in Tensorflow Lite.

This project deals with the detection of skin lesions within the ISICs dataset using YOLOv3 Object Detection with Darknet.

Implementation of the state of the art beat-detection, downbeat-detection and tempo-estimation model

This is a GUI interface which can process forest fire detection, smoke detection and fire segmentation

Cancer-and-Tumor-Detection-Using-Inception-model - In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks, specifically here the Inception model by google.

Hybrid CenterNet - Hybrid-supervised object detection / Weakly semi-supervised object detection

Sub-tomogram-Detection - Deep learning based model for Cyro ET Sub-tomogram-Detection

End-to-end face detection, cropping, norm estimation, and landmark detection in a single onnx model

Owner

MOT-Tracking-by-Detection-Pipeline - For Tracking-by-Detection format MOT (Multi Object Tracking), is it a framework that separates Detection and Tracking processes?

(JMLR'19) A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

Streaming Anomaly Detection Framework in Python (Outlier Detection for Streaming Data)

Human Detection - Pedestrian Detection using OpenCV Python

Yolo object detection - Yolo object detection with python

A Python Library for Graph Outlier Detection (Anomaly Detection)

Joint detection and tracking model named DEFT, or ``Detection Embeddings for Tracking.

LaneDet is an open source lane detection toolbox based on PyTorch that aims to pull together a wide variety of state-of-the-art lane detection models

A Data Annotation Tool for Semantic Segmentation, Object Detection and Lane Line Detection.(In Development Stage)

object detection; robust detection; ACM MM21 grand challenge; Security AI Challenger Phase VII