IEEE

A Novel ConvLSTM-Based U-net for Improved Brain Tumor Segmentation

Abstract: Using 2D scans or simple 3D convolutions are two limitations of previous works on segmentation of brain tumors by deep learning, which lead to ignoring the temporal distribution of the scans ...
IEEE

MLU-Net: A Multi-Level Lightweight U-Net for Medical Image Segmentation Integrating Frequency Representation and MLP-Based Methods

Abstract: Medical image segmentation is a challenging and popular task in the field of medical image processing in recent decades. Most of the current mainstream segmentation networks are based on ...
GitHub

U-Net: Semantic segmentation with PyTorch

Customized implementation of the U-Net in PyTorch for Kaggle's Carvana Image Masking Challenge from high definition images. This model was trained from scratch with 5k images and scored a Dice ...
GitHub

eminsafa/pytorch-cuda-compatibility

1.13.0 3.7+ 11.6, 11.7 0.13.0 0.14.0 1.12.1 3.7+ 10.2, 11.3, 11.6 0.12.1 0.13.1 1.12.0 3.7+ 10.2, 11.3, 11.6 0.12.0 0.13.0 1.11.0 3.6+ 10.2, 11.3 0.11.0 0.12.0 1.10.1 ...