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Single Channel Breast Segmentation Linknet
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Single Channel Breast Segmentation Linknet

Developed by AnikiFan
A PyTorch-based Linknet architecture implementation for semantic image segmentation, suitable for pixel-level classification tasks in fields like medical imaging
Image Segmentation
Safetensors
Open Source License:MIT#Medical Image Segmentation#ResNet Encoder#Breast Imaging Analysis
Downloads 16
Release Time : 10/15/2024

Model Overview

This model adopts the Linknet architecture combined with a pre-trained ResNet encoder, enabling efficient semantic image segmentation. It is particularly suitable for medical imaging analysis, such as breast tissue segmentation.

Model Features

Efficient Segmentation Architecture
Utilizes the lightweight Linknet architecture to maintain segmentation accuracy while improving computational efficiency
Pre-trained Encoder
Uses ImageNet pre-trained ResNet34 as the encoder to enhance feature extraction capabilities
Medical Imaging Optimization
Specially optimized for medical imaging data (e.g., breast tissue), demonstrating excellent performance on relevant datasets

Model Capabilities

Semantic Image Segmentation
Medical Imaging Analysis
Pixel-level Classification

Use Cases

Medical Imaging
Breast Tissue Segmentation
Used for segmenting tissue regions in breast medical images
Test set IoU reaches 0.76
Biomedical Research
Pathological Image Analysis
Assists pathologists in automatic segmentation of tissue samples
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