Cheap and reliable Node.js hosting starts at $3/month, and $1/month static HTML hosting

Created with love in Canada, visit hostnodejs.com today

Feel like to post an Ad? Learn Details

All Projects → fepegar → Torchio

fepegar / Torchio

Licence: apache-2.0

Medical image preprocessing and augmentation toolkit for deep learning

Programming Languages

python

139335 projects - #7 most used programming language

Labels

deep-learning machine-learning pytorch computer-vision convolutional-neural-networks cnn segmentation medical-imaging data-augmentation augmentation

Projects that are alternatives of or similar to Torchio

Data Science Bowl 2018

End-to-end one-class instance segmentation based on U-Net architecture for Data Science Bowl 2018 in Kaggle

Stars: ✭ 56 (-92.09%)

Mutual labels: convolutional-neural-networks, cnn, segmentation, medical-imaging

Cnn Interpretability

🏥 Visualizing Convolutional Networks for MRI-based Diagnosis of Alzheimer’s Disease

Stars: ✭ 68 (-90.4%)

Mutual labels: convolutional-neural-networks, cnn, medical-imaging

Niftynet

[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy

Stars: ✭ 1,276 (+80.23%)

Mutual labels: convolutional-neural-networks, segmentation, medical-imaging

Quicknat pytorch

PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty

Stars: ✭ 74 (-89.55%)

Mutual labels: convolutional-neural-networks, segmentation, medical-imaging

Miscnn

A framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning

Stars: ✭ 194 (-72.6%)

Mutual labels: convolutional-neural-networks, segmentation, medical-imaging

Fast Autoaugment

Official Implementation of 'Fast AutoAugment' in PyTorch.

Stars: ✭ 1,297 (+83.19%)

Mutual labels: convolutional-neural-networks, cnn, augmentation

Pba

Efficient Learning of Augmentation Policy Schedules

Stars: ✭ 461 (-34.89%)

Mutual labels: data-augmentation, convolutional-neural-networks, augmentation

Hyperdensenet

This repository contains the code of HyperDenseNet, a hyper-densely connected CNN to segment medical images in multi-modal image scenarios.

Stars: ✭ 124 (-82.49%)

Mutual labels: convolutional-neural-networks, cnn, segmentation

Livianet

This repository contains the code of LiviaNET, a 3D fully convolutional neural network that was employed in our work: "3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study"

Stars: ✭ 143 (-79.8%)

Mutual labels: convolutional-neural-networks, cnn, medical-imaging

Pytorch Saltnet

Kaggle | 9th place single model solution for TGS Salt Identification Challenge

Stars: ✭ 270 (-61.86%)

Mutual labels: convolutional-neural-networks, cnn, segmentation

Tf Pose Estimation

Deep Pose Estimation implemented using Tensorflow with Custom Architectures for fast inference.

Stars: ✭ 3,856 (+444.63%)

Mutual labels: convolutional-neural-networks, cnn

Neuralnetwork.net

A TensorFlow-inspired neural network library built from scratch in C# 7.3 for .NET Standard 2.0, with GPU support through cuDNN

Stars: ✭ 392 (-44.63%)

Mutual labels: convolutional-neural-networks, cnn

Learning Deep Learning

Paper reading notes on Deep Learning and Machine Learning

Stars: ✭ 388 (-45.2%)

Mutual labels: cnn, medical-imaging

Deeplogo

A brand logo detection system using tensorflow object detection API.

Stars: ✭ 388 (-45.2%)

Mutual labels: convolutional-neural-networks, cnn

Multi Class Text Classification Cnn

Classify Kaggle Consumer Finance Complaints into 11 classes. Build the model with CNN (Convolutional Neural Network) and Word Embeddings on Tensorflow.

Stars: ✭ 410 (-42.09%)

Mutual labels: convolutional-neural-networks, cnn

Deepface

Deep Learning Models for Face Detection/Recognition/Alignments, implemented in Tensorflow

Stars: ✭ 409 (-42.23%)

Mutual labels: convolutional-neural-networks, cnn

Dipy

DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.

Stars: ✭ 417 (-41.1%)

Mutual labels: segmentation, medical-imaging

Numpycnn

Building Convolutional Neural Networks From Scratch using NumPy

Stars: ✭ 436 (-38.42%)

Mutual labels: convolutional-neural-networks, cnn

Audiomentations

A Python library for audio data augmentation. Inspired by albumentations. Useful for machine learning.

Stars: ✭ 439 (-37.99%)

Mutual labels: data-augmentation, augmentation

Human Activity Recognition Using Cnn

Convolutional Neural Network for Human Activity Recognition in Tensorflow

Stars: ✭ 382 (-46.05%)

Mutual labels: convolutional-neural-networks, cnn

View All Similar Projects ➔

TorchIO

Tools like TorchIO are a symptom of the maturation of medical AI research using deep learning techniques.

Jack Clark, Policy Director at OpenAI (link).

Package
Docs
Build
Coverage
Code
Notebooks
Social

Original	Random blur

Random flip	Random noise

Random affine transformation	Random elastic transformation

Random bias field artifact	Random motion artifact

Random spike artifact	Random ghosting artifact

(Queue for patch-based training)

TorchIO is a Python package containing a set of tools to efficiently read, preprocess, sample, augment, and write 3D medical images in deep learning applications written in PyTorch, including intensity and spatial transforms for data augmentation and preprocessing. Transforms include typical computer vision operations such as random affine transformations and also domain-specific ones such as simulation of intensity artifacts due to MRI magnetic field inhomogeneity or k-space motion artifacts.

This package has been greatly inspired by NiftyNet, which is not actively maintained anymore.

Credits

If you like this repository, please click on Star!

If you use this package for your research, please cite the paper:

Pérez-García, F., Sparks, R., Ourselin, S.: TorchIO: a Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning. arXiv:2003.04696 [cs, eess, stat] (Mar 2020), http://arxiv.org/abs/2003.04696, arXiv: 2003.04696

BibTeX entry:

@article{perez-garcia_torchio_2020,
    title = {{TorchIO}: a {Python} library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning},
    shorttitle = {{TorchIO}},
    url = {http://arxiv.org/abs/2003.04696},
    urldate = {2020-03-11},
    journal = {arXiv:2003.04696 [cs, eess, stat]},
    author = {P{\'e}rez-Garc{\'i}a, Fernando and Sparks, Rachel and Ourselin, Sebastien},
    month = mar,
    year = {2020},
    note = {arXiv: 2003.04696},
    keywords = {Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning},
}

This project is supported by the Wellcome / EPSRC Centre for Interventional and Surgical Sciences (WEISS) (University College London) and the School of Biomedical Engineering & Imaging Sciences (BMEIS) (King's College London).

Getting started

See Getting started for installation instructions and a Hello, World! example.

Longer usage examples can be found in the notebooks.

All the documentation is hosted on Read the Docs.

Please open a new issue if you think something is missing.

Contributors

Thanks goes to all these people (emoji key):

_{Fernando Pérez-García} 💻 📖	_valabregue 🤔 👀 💻	_GFabien 💻 👀 🤔	_G.Reguig 💻	_{Niels Schurink} 💻	_{Ibrahim Hadzic} 🐛	_ReubenDo 🤔
_{Julian Klug} 🤔	_{David Völgyes} 🤔 💻	_{Jean-Christophe Fillion-Robin} 📖	_{Suraj Pai} 🤔	_{Ben Darwin} 🤔	_{Oeslle Lucena} 🐛	_{Soumick Chatterjee} 💻
_neuronflow 📖	_{Jan Witowski} 📖	_{Derk Mus} 📖 💻	_{Christian Herz} 🐛	_{Cory Efird} 💻	_{Esteban Vaca C.} 🐛	_{Ray Phan} 🐛
_{Akis Linardos} 🐛 💻	_{Nina Montana-Brown} 📖	_{fabien-brulport} 🐛	_malteekj 🐛	_{Andres Diaz-Pinto} 🐛

This project follows the all-contributors specification. Contributions of any kind welcome!

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].

Stars: ✭ 708

Visit Git Page 🔗Visit User Page 🔗Visit Issues Page (19) 🔗