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The mechanics of deformation in curved members, such as beams or arches, under bending moments, involve complex responses. When such a member, symmetric about the y-axis and shaped like a segment of a circle centered at point C, is subjected to equal and opposite forces, its curvature and surface lengths change significantly. This alteration results in the shift of the curvature's center from C to C', indicating a tighter curve.
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Related Experiment Video

Updated: Apr 15, 2026

A Volumetric Method for Quantification of Cerebral Vasospasm in a Murine Model of Subarachnoid Hemorrhage
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Accurate vessel segmentation with constrained B-snake.

Yuanzhi Cheng, Xin Hu, Ji Wang

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |April 11, 2015
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    Summary
    This summary is machine-generated.

    This study presents a new active contour model for accurate 3D vessel segmentation from CT scans. The framework effectively segments thin and low-contrast vessels, overcoming challenges like touching vessels and diseased portions.

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    Area of Science:

    • Medical Imaging
    • Image Segmentation
    • Computational Anatomy

    Background:

    • Accurate vascular segmentation is crucial for diagnosing and treating cardiovascular diseases.
    • Existing methods struggle with thin, low-contrast vessels, and complex anatomical regions like touching or diseased vessels.

    Purpose of the Study:

    • To develop an active contour framework for precise 3D vessel segmentation from computed tomography (CT) data.
    • To address limitations in segmenting challenging vascular structures, including thin, low-contrast, touching, and diseased vessels.

    Main Methods:

    • A multiscale vessel axis tracing approach in 3D CT data.
    • Vessel boundary delineation on cross-sectional planes with accurate shape and size constraints.
    • Active contour model with novel contour point detection and handling of problematic regions.

    Main Results:

    • The framework successfully segments thin and low-contrast vessels with high accuracy.
    • It effectively handles challenging regions, avoiding disconnected or incomplete segmentation.
    • Quantitative and qualitative evaluations show results comparable to manual segmentation.

    Conclusions:

    • The proposed active contour framework provides accurate and robust 3D vessel segmentation, particularly for challenging cases.
    • This method offers a significant advantage in clinical applications requiring precise vascular delineation.
    • The framework demonstrates superior performance compared to existing related methods.