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
Code for our EMNLP 2021 paper “Heterogeneous Graph Neural Networks for Keyphrase Generation”

GATER This repository contains the code for our EMNLP 2021 paper “Heterogeneous Graph Neural Networks for Keyphrase Generation”. Our implementation is

Jiacheng Ye 12 Nov 24, 2022
Six - a Python 2 and 3 compatibility library

Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the g

Benjamin Peterson 919 Dec 28, 2022
Reproduces ResNet-V3 with pytorch

ResNeXt.pytorch Reproduces ResNet-V3 (Aggregated Residual Transformations for Deep Neural Networks) with pytorch. Tried on pytorch 1.6 Trains on Cifar

Pau Rodriguez 481 Dec 23, 2022
Simple transformer model for CIFAR10

CIFAR-Transformer Simple transformer model for CIFAR10. Reference: https://www.tensorflow.org/text/tutorials/transformer https://github.com/huggingfac

9 Nov 07, 2022
CLIP+FFT text-to-image

Aphantasia This is a text-to-image tool, part of the artwork of the same name. Based on CLIP model, with FFT parameterizer from Lucent library as a ge

vadim epstein 690 Jan 02, 2023
TCNN Temporal convolutional neural network for real-time speech enhancement in the time domain

TCNN Pandey A, Wang D L. TCNN: Temporal convolutional neural network for real-time speech enhancement in the time domain[C]//ICASSP 2019-2019 IEEE Int

凌逆战 16 Dec 30, 2022
Code for the submitted paper Surrogate-based cross-correlation for particle image velocimetry

Surrogate-based cross-correlation (SBCC) This repository contains code for the submitted paper Surrogate-based cross-correlation for particle image ve

5 Jun 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
PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io

PyStan NOTE: This documentation describes a BETA release of PyStan 3. PyStan is a Python interface to Stan, a package for Bayesian inference. Stan® is

Stan 229 Dec 29, 2022
RSC-Net: 3D Human Pose, Shape and Texture from Low-Resolution Images and Videos

RSC-Net: 3D Human Pose, Shape and Texture from Low-Resolution Images and Videos Implementation for "3D Human Pose, Shape and Texture from Low-Resoluti

XiangyuXu 42 Nov 10, 2022
CVPRW 2021: How to calibrate your event camera

E2Calib: How to Calibrate Your Event Camera This repository contains code that implements video reconstruction from event data for calibration as desc

Robotics and Perception Group 104 Nov 16, 2022
Phy-Q: A Benchmark for Physical Reasoning

Phy-Q: A Benchmark for Physical Reasoning Cheng Xue*, Vimukthini Pinto*, Chathura Gamage* Ekaterina Nikonova, Peng Zhang, Jochen Renz School of Comput

29 Dec 19, 2022
Forecasting for knowable future events using Bayesian informative priors (forecasting with judgmental-adjustment).

What is judgyprophet? judgyprophet is a Bayesian forecasting algorithm based on Prophet, that enables forecasting while using information known by the

AstraZeneca 56 Oct 26, 2022
TorchMetrics is a collection of 25+ PyTorch metrics implementations and an easy-to-use API to create custom metrics.

Machine learning metrics for distributed, scalable PyTorch applications.

Pytorch Lightning 1.2k Jan 06, 2023
Proof-Of-Concept Piano-Drums Music AI Model/Implementation

Rock Piano "When all is one and one is all, that's what it is to be a rock and not to roll." ---Led Zeppelin, "Stairway To Heaven" Proof-Of-Concept Pi

Alex 4 Nov 28, 2021
Get started learning C# with C# notebooks powered by .NET Interactive and VS Code.

.NET Interactive Notebooks for C# Welcome to the home of .NET interactive notebooks for C#! How to Install Download the .NET Coding Pack for VS Code f

.NET Platform 425 Dec 25, 2022
People Interaction Graph

Gihan Jayatilaka*, Jameel Hassan*, Suren Sritharan*, Janith Senananayaka, Harshana Weligampola, et. al., 2021. Holistic Interpretation of Public Scenes Using Computer Vision and Temporal Graphs to Id

University of Peradeniya : COVID Research Group 1 Aug 24, 2022
implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks

YOLOR implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks To reproduce the results in the paper, please us

Kin-Yiu, Wong 1.8k Jan 04, 2023
Tensors and Dynamic neural networks in Python with strong GPU acceleration

PyTorch is a Python package that provides two high-level features: Tensor computation (like NumPy) with strong GPU acceleration Deep neural networks b

61.4k Jan 04, 2023
ICNet for Real-Time Semantic Segmentation on High-Resolution Images, ECCV2018

ICNet for Real-Time Semantic Segmentation on High-Resolution Images by Hengshuang Zhao, Xiaojuan Qi, Xiaoyong Shen, Jianping Shi, Jiaya Jia, details a

Hengshuang Zhao 594 Dec 31, 2022