LEADER 04098nam 22007695 450 001 996647864403316 005 20250207115241.0 010 $a9783031808715 010 $a3031808711 024 7 $a10.1007/978-3-031-80871-5 035 $a(MiAaPQ)EBC31900206 035 $a(Au-PeEL)EBL31900206 035 $a(CKB)37498921700041 035 $a(DE-He213)978-3-031-80871-5 035 $a(OCoLC)1500772404 035 $a(EXLCZ)9937498921700041 100 $a20250207d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDiabetic Foot Ulcers Grand Challenge $e4th Challenge, DFUC 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings /$fedited by Moi Hoon Yap, Connah Kendrick, Raphael Brüngel 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (190 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v15335 311 08$a9783031808708 311 08$a3031808703 327 $aTranslating 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. 330 $aThis book constitutes the 4th Challenge on Diabetic Foot Ulcers, DFUC2024, held in conjunction with the 27th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2024, in Marrakesh, Morocco, on October 6, 2024. The 8 full papers presented in this book together with 2 invited papers were carefully reviewed and selected from 11 submissions. The task of DFUC 2024 was on self-supervised learning in ulcer segmentation, for the purpose of supporting research towards more advanced methods to overcome data deficiency and unlabelled data. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v15335 606 $aComputer vision 606 $aImage processing$xDigital techniques 606 $aSignal processing 606 $aMachine learning 606 $aApplication software 606 $aEducation$xData processing 606 $aComputer Vision 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aSignal, Speech and Image Processing 606 $aMachine Learning 606 $aComputer and Information Systems Applications 606 $aComputers and Education 615 0$aComputer vision. 615 0$aImage processing$xDigital techniques. 615 0$aSignal processing. 615 0$aMachine learning. 615 0$aApplication software. 615 0$aEducation$xData processing. 615 14$aComputer Vision. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aSignal, Speech and Image Processing. 615 24$aMachine Learning. 615 24$aComputer and Information Systems Applications. 615 24$aComputers and Education. 676 $a006.37 700 $aYap$b Moi Hoon$01762001 701 $aKendrick$b Connah$01762002 701 $aBrüngel$b Raphael$01785857 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996647864403316 996 $aDiabetic Foot Ulcers Grand Challenge$94317307 997 $aUNISA