UID:
almahu_9949985932802882
Umfang:
X, 125 p. 46 illus., 44 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2025.
ISBN:
9783031808715
Serie:
Lecture Notes in Computer Science, 15335
Inhalt:
This book constitutes the 4th Challenge on Diabetic Foot Ulcers, DFUC2024, held in conjunction with the 27th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2024, in Marrakesh, Morocco, on October 6, 2024. The 8 full papers presented in this book together with 2 invited papers were carefully reviewed and selected from 11 submissions. The task of DFUC 2024 was on self-supervised learning in ulcer segmentation, for the purpose of supporting research towards more advanced methods to overcome data deficiency and unlabelled data.
Anmerkung:
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.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9783031808708
Weitere Ausg.:
Printed edition: ISBN 9783031808722
Sprache:
Englisch
DOI:
10.1007/978-3-031-80871-5
URL:
https://doi.org/10.1007/978-3-031-80871-5
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