Diabetic Foot Ulcers Grand Challenge

Translating Clinical Delineation of Diabetic Foot Ulcers into Machine Interpretable Segmentation.- Dinov2 Mask R-CNN: Self-supervised Instance Segmentation of Diabetic Foot Ulcers.- Diabetic foot ulcer unsupervised segmentation with Vision Transformers attention.- Self-Supervised Instance Segmentation of Diabetic Foot Ulcers via Feature Correspondence Distillation.- Multi-stage Segmentation of Diabetic Foot Ulcers Using Self-Supervised Learning.- SSL-based Encoder Pre-training for Segmenting a Heterogeneous Chronic Wound Image Database with Few Annotations.- Multi-Scale Attention Network for Diabetic Foot Ulcer Segmentation using Self-Supervised Learning.- A Supervised Segmentation Solution: Diabetic Foot Ulcers Challenge 2024.- CDe: Focus on the Color Differences in Diabetic Foot Images.- Diabetic Foot Ulcer Grand Challenge 2024: Overview and Baseline Methods.

Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.

• Processamento de imagens
• Visão por computador
• Engenharia electrónica
• Processamento de sinais
• Aprendizagem mecânica
• Tecnologia da informação: aspectos gerais
• Equipamentos e tecnologia educacional, computer-aided learning (CAL)

Instance segmentation;synthetic images;self-supervised learning;diabetic foot ulcers;machine learning;image processing;computer vision