TorchIO: a Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning

We present TorchIO, an open-source Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images for deep learning. It follows the design of PyTorch and relies on standard medical image processing libraries such as SimpleITK or NiBabel to efficiently process large 3D images during the training of convolutional neural networks. We provide multiple generic as well as magnetic-resonance-imaging-specific operations for preprocessing and augmentation of medical images. TorchIO is an open-source project with code, comprehensive examples and extensive documentation shared at https://github.com/fepegar/torchio.

READ FULL TEXT

page 7

page 9

page 10

research
10/21/2019

MIScnn: A Framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning

The increased availability and usage of modern medical imaging induced a...
research
02/25/2019

Data augmentation using learned transforms for one-shot medical image segmentation

Biomedical image segmentation is an important task in many medical appli...
research
04/12/2023

SAMM (Segment Any Medical Model): A 3D Slicer Integration to SAM

The Segment Anything Model (SAM) is a new image segmentation tool traine...
research
07/12/2023

Towards a privacy-preserving distributed cloud service for preprocessing very large medical images

Digitized histopathology glass slides, known as Whole Slide Images (WSIs...
research
08/28/2023

Reinforcement Learning for Sampling on Temporal Medical Imaging Sequences

Accelerated magnetic resonance imaging resorts to either Fourier-domain ...
research
03/26/2021

Evaluation of Preprocessing Techniques for U-Net Based Automated Liver Segmentation

To extract liver from medical images is a challenging task due to simila...
research
11/18/2019

Multi-modal Deep Guided Filtering for Comprehensible Medical Image Processing

Deep learning-based image processing is capable of creating highly appea...

Please sign up or login with your details

Forgot password? Click here to reset