prostate-segmentation

A JAX-based deep learning framework for image segmentation using diffusion models.

Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound

Asymmetric Multi-Task Attention Network for Prostate Bed Segmentation in CT Images

Domain Generalization for Prostate Segmentation in Transrectal Ultrasound Images: A Multi-center Study

A deep semi-supervised method (UATS) for medical segmentation

TensorFlow implementation of our paper: "Automated detection of aggressive and indolent prostate cancer on magnetic resonance imaging [Medical Physics 2021]".

A quality control system for automated prostate segmentation on T2-weighted MRI

This repository implements a robust deep learning method (LFBNet) for medical image segmentation using a two systems approach. Learning fast and slow strategy for robust medical image analysis.

Medical Image Segmentation: Developed a U-Net architecture for automated prostate cancer detection in MRI scans using PyTorch.

VGG16-UNet vs LoRA-fine-tuned MedSAM for prostate segmentation on micro-ultrasound

Lightweight 3D Medical Image Segmentation pipeline optimized for low-VRAM GPUs (<8GB). Uses a Multi-Decoder U-Net to segment pelvic organs from CT data.

This repository contains the work done as a part of the RnD course taken under Prof. Amit Sethi of EE Department at IITB

Pytorch implementation of carcino-net

Parameter-efficient LoRA fine-tuning of MedSAM (ViT-B) for prostate segmentation, achieving 95.7% Dice and 91.9% IoU.

VGG16-UNet vs LoRA-fine-tuned MedSAM for prostate segmentation on micro-ultrasound

Prostate segmentation of T2 weighted Magnetic Resonance Images using Deep Learning methods with full data acquisition and preprocessing pipeline.

Segment the Prostate 3D data set with the UNet3D

Hybrid VGG16-UNet for automated prostate segmentation on micro-ultrasound images.

A simple module for prostate segmentation in MRI T2-W images

🏞️ Make your images load faster. A better save for the web.