This repository is an unoffical PyTorch implementation of Medical segmentation in 2D and 3D.
Automatically segment the liver and liver tumors in CT scans with 3D-UNET
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.
Convert a directory of DICOM images to a consolidated NumPy array
My submission to the MICCAI Educational Challenge 2020.
Proyecto Final Integrador Ingeniería Biomédica - Deep Learning para segmentación y clasificación de imágenes médicas
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...