Generalized Surface Flows for Deformable Registration and Cortical Matching 1st Edition by I Eckstein, A A Joshi, CJ Kuo, R Leahy, M Desbrun ISBN 9783540757573

Generalized Surface Flows for Deformable Registration and Cortical Matching 1st Edition by I Eckstein, A A Joshi, CJ Kuo, R Leahy, M Desbrun – Ebook PDF Instant Download/Delivery. 9783540757573
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ISBN 13: 9783540757573
Author: I Eckstein, A A Joshi, CJ Kuo, R Leahy, M Desbrun

Despite being routinely required in medical applications, deformable surface registration is notoriously difficult due to large intersubject variability and complex geometry of most medical datasets. We present a general and flexible deformable matching framework based on generalized surface flows that efficiently tackles these issues through tailored deformation priors and multiresolution computations. The value of our approach over existing methods is demonstrated for automatic and user-guided cortical registration.

Generalized Surface Flows for Deformable Registration and Cortical Matching 1st Table of contents:

• Introduction
  1.1 Motivation and Background
  1.2 Problem Definition and Objectives
  1.3 Key Contributions of the Paper
  1.4 Structure of the Paper

• Preliminaries
  2.1 Surface-Based Registration: Overview and Importance
  2.2 Deformable Registration Techniques
  2.3 Cortical Matching in Neuroimaging
  2.4 Related Work on Surface Flows and Registration Methods

• Generalized Surface Flows
  3.1 Mathematical Foundations of Surface Flows
  3.2 Generalized Surface Flow Models for Deformable Registration
  3.3 Properties and Advantages of Surface Flows
  3.4 Modeling Deformations with Surface Flows
  3.5 Numerical Methods for Computing Surface Flows

• Deformable Registration Using Surface Flows
  4.1 Problem Setup and Assumptions
  4.2 Surface Flow Algorithms for Deformable Registration
  4.3 Registration of Surfaces with Different Topologies
  4.4 Optimization Strategies for Surface Flow-Based Registration

• Cortical Matching and Its Application
  5.1 Overview of Cortical Matching in Brain Imaging
  5.2 Matching Cortical Surfaces Across Subjects
  5.3 Techniques for Aligning Cortical Landmarks
  5.4 Evaluation of Cortical Matching Performance
  5.5 Handling Variability in Cortical Anatomy

• Methodology
  6.1 Data Acquisition and Preprocessing for Cortical Surfaces
  6.2 Surface Flow-Based Deformable Registration Framework
  6.3 Integration of Cortical Matching and Surface Flow Models
  6.4 Algorithmic Implementation and Computational Requirements

• Evaluation and Results
  7.1 Experimental Setup and Datasets Used
  7.2 Performance Metrics for Deformable Registration and Matching
  7.3 Comparative Results with Other Registration Methods
  7.4 Case Studies in Cortical Surface Matching

• Applications in Neuroimaging and Brain Mapping
  8.1 Impact on Structural Brain Mapping and Morphometry
  8.2 Functional Imaging and Cortical Activity Mapping
  8.3 Potential Applications in Neurological Disorders (e.g., Alzheimer’s, Schizophrenia)
  8.4 Cortical Surface Registration in Longitudinal Studies

• Discussion
  9.1 Insights from Surface Flow-Based Registration and Cortical Matching
  9.2 Limitations and Challenges in the Current Approach
  9.3 Open Problems and Future Directions in Surface Flow Models
  9.4 Opportunities for Integration with Other Neuroimaging Modalities

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