Medical imaging processing for AI applications.

This repository is an unoffical PyTorch implementation of Medical segmentation in 2D and 3D.

3D Slicer module for TorchIO.

Automatically segment the liver and liver tumors in CT scans with 3D-UNET

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Mean Teacher with Medical Imaging Data Augmentation (torchio)

An end to end automatic segmentation tool for MRI files, that can identify lungs, bladder, liver, kidney and bone

Automatic segmentation of the liver and liver tumors in CT scans with 3D U-Net.

An implementation of the BigAug augmentation pipeline compatible with the torchio package

Convert a directory of DICOM images to a consolidated NumPy array

My submission to the MICCAI Educational Challenge 2020.

It aims to remove artifacts from MR images. It does the preprocessing of the datasets, including the generation of artifacts by using TorchIO, as well as the training of super resolution convolutional neural networks and some posterior aspects to their analysis.

Container for data used by TorchIO

A conda-smithy repository for torchio.

In this tutorial, we will cover the basics of using TorchIO by loading and viewing some MRIs and applying various transformations. We will use single-channel T2-FLAIR NIfTI samples from the ASNR-RSNA-MICCAI Africa Dataset of Brain MRI with tumors. This tutorial can be followed in a script, or notebook of sort (Colab, Jupyter, etc).

Facial and temporal artery segmentation in CT data using TorchIO and MONAI.

This repository implements a 3D U-Net model for segmenting HIE lesions in neonatal MRI scans, exploring various loss functions including Dice, Dice-Focal, Tversky, Hausdorff Distance, and hybrid loss functions. BONBID-HIE dataset is used for this study.

A full implementation of unet3d model with torchio on ixi_tiny dataset

3D U-Net–based medical image segmentation pipeline built with PyTorch, TorchIO, and PyTorch Lightning.

Pieces of the nnU-Net framework recreated using widely used libraries such as TorchIO and MONAI

AI-based 3D depth sensing from stereo vision systems

RectoMap is a deep learning pipeline for segmenting rectal cancer and mesorectum from T2-weighted MRI and predicting pathological complete response (pCR) after neoadjuvant therapy

Learning TorchIO

A command-line flashlight program for the Nokia N900

🌏 Official Al Torchio Antico hotel-restourant website

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Config files for my GitHub profile.

A modern video cutting and converting app

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A library for accessing torch serialized files