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Computational Biomechanics for Medicine [electronic resource] : Challenges and Solutions in Computing / edited by Adam Wittek, Magdalena Kobielarz, Anju R. Babu, Martyn P. Nash, Poul M. F. Nielsen, Karol Miller.

Contributor(s): Material type: TextSeries: Lecture Notes in BioengineeringPublisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edition: 1st ed. 2024Description: X, 168 p. 73 illus., 71 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031646324
Subject(s):
Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleLOC classification:
  • R856-857
  • QH513
Online resources:
Contents:
Diffeomorphic Multi-Resolution Deep Learning Registration for Applications in Breast MRI -- Random Boundaries: Quantifying Segmentation Uncertainty in Solutions to Boundary-Value Problems -- Open Meshed Anatomy -- Developing a Pipeline to Efficiently Represent MNI-Based Brain Functional Regions For FE Modeling -- Investigating the Impact of Material Properties on the Simulated Response of Heel Soft Tissue in the Context of Pressure Ulcers.
In: Springer Nature eBookSummary: This book presents peer-reviewed contributions from the MICCAI 2023 Computational Biomechanics for Medicine CBM XVIII Workshop held in conjunction with the 26th International MICCAI Conference. The content focuses on applications of computational biomechanics to computer-integrated medicine, which includes medical image computing, application of machine learning in image analysis and biomechanics, atlas based biomechanical simulations, novel algorithms of computational biomechanics and experimental methods for analysis of disease and injury mechanisms. The book details state-of-the-art progress in the above fields to researchers, students, and professionals.
Item type: List(s) this item appears in: Titluri cărți electronice Springer Nature 2025 (10631 titluri)
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Diffeomorphic Multi-Resolution Deep Learning Registration for Applications in Breast MRI -- Random Boundaries: Quantifying Segmentation Uncertainty in Solutions to Boundary-Value Problems -- Open Meshed Anatomy -- Developing a Pipeline to Efficiently Represent MNI-Based Brain Functional Regions For FE Modeling -- Investigating the Impact of Material Properties on the Simulated Response of Heel Soft Tissue in the Context of Pressure Ulcers.

This book presents peer-reviewed contributions from the MICCAI 2023 Computational Biomechanics for Medicine CBM XVIII Workshop held in conjunction with the 26th International MICCAI Conference. The content focuses on applications of computational biomechanics to computer-integrated medicine, which includes medical image computing, application of machine learning in image analysis and biomechanics, atlas based biomechanical simulations, novel algorithms of computational biomechanics and experimental methods for analysis of disease and injury mechanisms. The book details state-of-the-art progress in the above fields to researchers, students, and professionals.

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