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2D and 3D Vascular Structures Enhancement via Multiscale Fractional Anisotropy Tensor

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abstract

The detection of vascular structures from noisy images is a fundamental process for extracting meaningful information in many applications. Most well-known vascular enhancing techniques often rely on Hessian-based filters. This paper investigates the feasibility and deficiencies of detecting curve-like structures using a Hessian matrix. The main contribution is a novel enhancement function, which overcomes the deficiencies of established methods. Our approach has been evaluated quantitatively and qualitatively using synthetic examples and a wide range of real 2D and 3D biomedical images. Compared with other existing approaches, the experimental results prove that our proposed approach achieves high-quality curvilinear structure enhancement.

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2025 1

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Vessel segmentation for X-separation

cs.CV · 2025-02-03 · conditional · novelty 6.0

A pipeline combining MFAT vesselness, MIP-based seeds, and geometry-guided region growing achieves the highest Dice scores for vessel segmentation on chi-separation brain maps.

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  • Vessel segmentation for X-separation cs.CV · 2025-02-03 · conditional · none · ref 48 · internal anchor

    A pipeline combining MFAT vesselness, MIP-based seeds, and geometry-guided region growing achieves the highest Dice scores for vessel segmentation on chi-separation brain maps.