Single-channel breast segmentation Unet open-source image segmentation model - Supports multiple architectures and is suitable for semantic segmentation tasks

Single Channel Breast Segmentation Unet

Developed by AnikiFan

PyTorch-based Unet image segmentation model supporting various encoder architectures, suitable for semantic segmentation tasks

Image Segmentation

Safetensors

Open Source License:MIT #Medical Image Segmentation #ResNet Encoder #Breast Lesion Detection

Downloads 65

Release Time : 10/15/2024

Model Overview

This is a PyTorch-implemented Unet architecture image segmentation model primarily used for semantic segmentation tasks. The model supports multiple pretrained encoders and provides flexible configuration options.

Model Features

Multiple Encoder Support

Supports mainstream encoder architectures like ResNet and can load ImageNet pretrained weights

Flexible Configuration Options

Customizable encoder depth, decoder channels, attention mechanisms, and other parameters

Batch Normalization Support

Decoder supports batch normalization layers, aiding training stability and model performance

Model Capabilities

Image Segmentation

Semantic Segmentation

Medical Image Analysis

Use Cases

Medical Imaging

Breast Image Segmentation

Used for segmentation tasks in breast medical images

Achieved IOU of 0.757 on test dataset

Featured Recommended AI Models

Empowering the Future, Your AI Solution Knowledge Base

English 简体中文繁體中文にほんご

Single Channel Breast Segmentation Unet

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 Unet Model Card

🚀 Quick Start

Load trained model

✨ Features

Model init parameters

Model metrics

Dataset

📚 Documentation

📄 License