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Shape in Medical Imaging : International Workshop, ShapeMI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings / edited by Christian Wachinger, Beatriz Paniagua, Shireen Elhabian, Gijs Luijten, Jan Egger.

Springer Nature - Springer Computer Science (R0) eBooks 2025 English International Available online

Springer Nature - Springer Computer Science (R0) eBooks 2025 English International
Format:
Book
Author/Creator:
Wachinger, Christian.
Contributor:
Paniagua, Beatriz.
Elhabian, Shireen.
Luijten, Gijs.
Egger, Jan.
Series:
Lecture Notes in Computer Science, 1611-3349 ; 15275
Language:
English
Subjects (All):
Computer vision.
Machine learning.
Computers, Special purpose.
Computer Vision.
Machine Learning.
Special Purpose and Application-Based Systems.
Local Subjects:
Computer Vision.
Machine Learning.
Special Purpose and Application-Based Systems.
Physical Description:
1 online resource (236 pages)
Edition:
1st ed. 2025.
Place of Publication:
Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Summary:
This book constitutes the proceedings of the International Workshop on Shape in Medical Imaging, ShapeMI 2024, which took place in Marrakesh, Morocco, on October 6, 2024, held in conjunction with MICCAI 2024. The 16 full papers included in this book were carefully reviewed and selected from 24 submissions. They focus on shape and spectral analysis, geometric learning and modeling algorithms, and application-driven research.
Contents:
Weakly Supervised Bayesian Shape Modeling from Unsegmented Medical Images
PSGMM: Pulmonary Segment Segmentation Based on Gaussian Mixture Model
Deformable vertebra 3D/2D registration from biplanar X-rays using particle-based shape modelling
Deep Combined Computing of Vascular Images with Tubular Shape-Guided Convolution
Implicitly Explicit: Segmenting Vertebrae with Deep Implicit Statistical Shape Models
3D Body Twin: Improving Human Gait Visualizations Using Personalized Avatars
Robust Curve Detection in Volumetric Medical Imaging via Attraction Field
A Critical Comparison Between Template-Based and Architecture-Reused Deep Learning Methods for Generic 3D Landmarking of Anatomical Structures
Adaptive Bi-ventricle Surface Reconstruction from Cardiovascular Imaging
Application of Deep Statistical Shape Modeling for Analysis of Obstructive Sleep Apnea from MRI Data
Leveraging Expert Knowledge for Real-time Online Adaptation of Intraoperative Liver Registration
MASSM: An End-to-End Deep Learning Framework for Multi-Anatomy Statistical Shape Modeling Directly From Images
LaMoD: Latent Motion Diffusion Model For Myocardial Strain Generation
Enhancing Multimodal Image-Based Classification of Alzheimer’s Disease with Surface Information
Fast Medical Shape Reconstruction via Meta-learned Implicit Neural Representations
Towards Point Cloud-Based Medical Image Registration for Dynamic 4D-CT Imaging.
Notes:
Description based on publisher supplied metadata and other sources.
ISBN:
3-031-75291-0
OCLC:
1465265743

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