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Related Concept Videos

Deformations in a Transverse Cross Section01:21

Deformations in a Transverse Cross Section

759
When a material is subjected to uniaxial stress, it elongates or contracts in the direction of the applied force, and also undergoes changes in the perpendicular directions. This behavior is crucial for understanding how materials behave under stress and is governed by mechanical properties such as Poisson's ratio v, which measures the ratio of transverse strain to axial strain.
As the material stretches, it expands or contracts in orthogonal directions to the load. This phenomenon varies...
759

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Related Experiment Video

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Three-Dimensional Shape Modeling and Analysis of Brain Structures
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Hippocampal Shape Modeling Based on a Progressive Template Surface Deformation and its Verification.

Jaeil Kim, Maria Del C Valdes-Hernandez, Natalie A Royle

    IEEE Transactions on Medical Imaging
    |December 23, 2014
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    Summary

    This study introduces a novel mesh-to-volume registration method for accurate hippocampal shape recovery and anatomical correspondence. The approach effectively reconstructs smooth surfaces and detects subtle shape changes related to cognitive abilities and neurodegenerative diseases.

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    Area of Science:

    • Neuroimaging
    • Medical Image Analysis
    • Computational Anatomy

    Background:

    • Accurate hippocampal shape recovery and anatomical correspondence are crucial for understanding brain structure and function.
    • Existing methods struggle with rough segmentations and establishing reliable correspondences.

    Purpose of the Study:

    • To develop and evaluate a mesh-to-volume registration approach for robust hippocampal shape reconstruction and correspondence.
    • To assess the method's sensitivity in detecting shape differences in mild cognitive impairment and Alzheimer's disease.
    • To explore its applicability in identifying shape changes related to cognitive abilities.

    Main Methods:

    • A progressive model deformation technique using flexible weighting and multi-level neighborhood for vertex connectivity.
    • Large-to-small scale deformation of a template surface to minimize geometric distortion.
    • Comparison with SPHARM-PDM, ShapeWorks, and LDDMM using shape similarity, surface roughness, volume, and deformity metrics.

    Main Results:

    • The proposed method generated smoother surfaces with reduced volume differences and superior shape similarity compared to existing methods.
    • It demonstrated robustness in constructing anatomical correspondences between individual hippocampal models.
    • Statistical analyses confirmed its sensitivity in detecting subtle hippocampal shape changes associated with clinical variables.

    Conclusions:

    • The developed mesh-to-volume registration method offers accurate and robust hippocampal shape recovery and correspondence.
    • It shows promise for neuroimaging research, particularly in identifying subtle shape alterations in neurological and cognitive conditions.
    • The method outperforms established techniques in surface reconstruction and shape similarity.