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Related Experiment Video

Updated: Feb 22, 2026

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

Subject-Specific Longitudinal Shape Analysis by Coupling Spatiotemporal Shape Modeling with Medial Analysis.

Sungmin Hong¹, James Fishbaugh¹, Morteza Rezanejad²

¹Computer Science and Engineering, Tandon School of Engineering, New York University.

Proceedings of Spie--The International Society for Optical Engineering

|October 3, 2017

Summary

This study introduces a novel framework for analyzing disease-related anatomical changes over time. By combining spatiotemporal deformations with medial surface analysis, it quantifies degeneration distinct from normal aging.

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Area of Science:

Medical imaging analysis
Computational anatomy
Biomedical engineering

Background:

Longitudinal shape analysis is crucial for understanding disease progression.
Anatomical changes can result from aging, disease, or external structural influences.
Accurate modeling of subject-specific shape change remains a significant challenge.

Purpose of the Study:

To develop a framework for analyzing disease-related shape changes.
To differentiate disease-induced degeneration from normal aging.
To enable quantitative analysis of localized degeneration.

Main Methods:

Coupling extrinsic modeling (spatiotemporal deformations) with intrinsic shape properties (medial surface analysis).
Comparing subject-specific shape trajectories to a normative 4D shape atlas of normal aging.
Establishing inter/intra-subject anatomical correspondence for robust comparisons.

Main Results:

The framework enables separate quantification of disease-related shape changes.
It provides localized measurements of degeneration by analyzing intrinsic shape properties.
Demonstrated on Huntington's disease subjects, showing potential for quantitative and qualitative comparisons.

Conclusions:

The proposed framework effectively models extrinsic and intrinsic shape changes for disease analysis.
It allows for the separation of disease-related degeneration from normal aging.
This approach facilitates a deeper understanding of neurodegenerative disease progression through quantitative shape analysis.