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Three-Dimensional Shape Modeling and Analysis of Brain Structures
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Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

Size and shape recognition using measurement statistics and random 3D reference structures.

Arnab Sinha, David Brady

    Optics Express
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    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a lensless 3D imaging system using reference structures. The system estimates object size and shape from projection statistics, avoiding physical image formation for advanced 3D reconstruction.

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    Clinical Anthropometrics and Body Composition from 3-Dimensional Optical Imaging
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    Area of Science:

    • Optics and Photonics
    • Computational Imaging
    • 3D Reconstruction

    Background:

    • Traditional 3D imaging often requires complex optics and physical image formation.
    • Lensless imaging offers a simplified approach but faces challenges in reconstructing 3D information.
    • Reference structures can encode spatial information for improved 3D analysis.

    Purpose of the Study:

    • To develop and validate a lensless 3D imaging system utilizing reference structures.
    • To demonstrate the estimation of object size and shape from measurement statistics.
    • To explore the potential of this method for 3D shape recognition.

    Main Methods:

    • Designing a lensless 3D imaging system with a sensor array.
    • Implementing three dimensional (3D) reference structures to segment source spaces.
    • Deriving and experimentally verifying a model for projection statistics.
    • Analyzing measurement statistics for size and shape estimation.

    Main Results:

    • A model was derived and experimentally verified to predict projection statistics.
    • Accurate object size estimation was achieved using measurement statistics without physical image formation.
    • Preliminary experiments show potential for 3D shape recognition using measured statistics.

    Conclusions:

    • Lensless 3D imaging systems can leverage reference structures and measurement statistics for dimensional analysis.
    • This approach offers a novel pathway for size estimation and 3D shape recognition.
    • Further research can expand the application of this technique in 3D reconstruction.