There are 3 repositories under skin-lesion-segmentation topic.
BCDU-Net : Medical Image Segmentation
[WACV 2024] Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image Segmentation
[MICCAI 2021] Boundary-aware Transformers for Skin Lesion Segmentation
HiFormer: Hierarchical Multi-scale Representations Using Transformers for Medical Image Segmentation (WACV 2023)
Transfer Learning with DCNNs (DenseNet, Inception V3, Inception-ResNet V2, VGG16) for skin lesions classification on HAM10000 dataset largescale data.
Official implementation code for Attention Swin U-Net: Cross-Contextual Attention Mechanism for Skin Lesion Segmentation paper
[MICCAI 2023] DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineation
Skin lesion segmentation is one of the first steps towards automatic Computer-Aided Diagnosis of skin cancer. Vast variety in the appearance of the skin lesion makes this task very challenging. The contribution of this paper is to apply a power foreground extraction technique called GrabCut for automatic skin lesion segmentation in HSV color space with minimal human interaction. Preprocessing was performed for removing the outer black border. Jaccard Index was measured to evaluate the performance of the segmentation method. On average, 0.71 Jaccard Index was achieved on 1000 images from ISIC challenge 2017 Training Dataset.
A Hybrid CNN-Transformer Architecture for Precise Medical Image Segmentation
Based on our paper on skin lesion segmentation: "MFSNet: A Multi Focus Segmentation Network for Skin Lesion Segmentation"
This is the code corresponding to our CVPR ISIC 2020 paper.
PyTorch implementation of DoubleUNet for medical image segmentation
Matthews Correlation Coefficient Loss implementation for image segmentation.
Datasets for skin image analysis
This repository contains the code for semantic segmentation of the skin lesions on the ISIC-2018 dataset using TensorFlow 2.0.
Attention Squeeze U-Net
Skin lesion classification, using Keras and the ISIC 2020 dataset
Human Facial Skin Defects Dataset
Implementation of U-Net / DoubleU-Net for lesion boundary Segmentation (ISIC 2018-task 1)
Exploring the inter-annotator agreement between ISIC Archive segmentation masks
Code corresponding to our MICCAI SASHIMI 2019 paper on shape-constrained skin lesion image synthesis.
Analysis of Skin Lesion Images to segment lesion regions and classify lesion type using adversarial deep learning.
DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineation - MICCAI 2023 PRIME Workshop