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Supervised and Semi-supervised Multi-structure Segmentation and Landmark Detection in Dental Data MICCAI 2024 Challenges: ToothFairy 2024, 3DTeethLand 2024, and STS 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings /

This book constitutes three challenges that were 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: ToothFairy challenge(ToothFairy2: Multi-Structure Segmentation in CBCT Vo...

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Detalles Bibliográficos
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Wang, Yaqi (Editor), Qian, Dahong (Editor), Wang, Shuai (Editor), Ben-Hamadou, Achraf (Editor), Pujades, Sergi (Editor), Lumetti, Luca (Editor), Grana, Costantino (Editor), Bolelli, Federico (Editor)
Formato: Electrónico eBook
Lenguaje:inglés
Publicado: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Edición:1st ed. 2025.
Colección:Lecture Notes in Computer Science, 15571
Materias:
Image processing > Digital techniques.
Computer vision.
Computers.
Application software.
Machine learning.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Computing Milieux.
Computer and Information Systems Applications.
Machine Learning.
Acceso en línea:https://doi.org/10.1007/978-3-031-88977-6
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Sumario:This book constitutes three challenges that were 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: ToothFairy challenge(ToothFairy2: Multi-Structure Segmentation in CBCT Volumes), Semi-supervised Teeth Segmentation (STS 2024), and the 3DTeethLand (3D Teeth Landmarks Detection Challenge). The 21 papers presented in this volume were carefully reviewed and selected from 28 submissions. ToothFairy challenges focused on the development of deep learning frameworks to segment anatomical structures in CBCTs by incrementally extending the amount of publicly available 3D-annotated CBCT scans and providing the first publicly available fully annotated datasets. The STS Challenge promoted the development of teeth segmentation in panoramic X-ray images and CBCT scans. It also provided instance annotations for different teeth, including pertinent category information. The 3DTeethLand24 Challenge played a key role in advancing automation and leveraging AI to optimize orthodontic treatments. It also aims to tackle the challenge of limited access to data, providing a valuable resource that encourages community engagement in this vital area with potential clinical implications.
Descripción Física:XVII, 242 p. 77 illus., 72 illus. in color. online resource.
ISBN:9783031889776
ISSN:1611-3349 ;
DOI:10.1007/978-3-031-88977-6

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