Point Cloud Registration for Measuring Shape Dependence of Soft Tissue Deformation by Digital Twins in Head and Neck Surgery

Point Cloud Registration for Measuring Shape Dependence of Soft Tissue Deformation by Digital Twins in Head and Neck Surgery

Introduction: A 2½ D point cloud registration method was developed to generate digital twins of different tissue shapes and resection cavities by applying a machine learning (ML) approach. This demonstrates the feasibility of quantifying soft tissue shifts. Methods: An ML model was trained using sim...

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Bibliographic Details
Main Authors: Sara Monji-Azad, David Männle, Jürgen Hesser, Jan Pohlmann, Nicole Rotter, Annette Affolter, Cleo Aron Weis, Sonja Ludwig, Claudia Scherl
Format: Article
Language:English
Published: Karger Publishers 2024-01-01
Series:Biomedicine Hub
Subjects:
point cloud registration
digital twin
artificial intelligence
tissue shift
head and neck surgery
Online Access:https://beta.karger.com/Article/FullText/535421

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https://beta.karger.com/Article/FullText/535421

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