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A Benchmark Framework for Multiregion Analysis of Vesselness Filters.

Jonas Lamy, Odyssee Merveille, Bertrand Kerautret

    IEEE Transactions on Medical Imaging
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    Choosing the best vesselness filter for angiographic image processing is challenging. This study introduces a benchmark framework to compare seven filters across multiple datasets, aiding researchers in selecting optimal parameters for vessel segmentation.

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    Area of Science:

    • Medical image analysis
    • Computer vision
    • Vascular imaging

    Background:

    • Vesselness filters enhance tubular structures in angiographic images for segmentation.
    • Selecting appropriate filters and parameters is complex and requires expertise.
    • Existing benchmarks for comparing vesselness filters are limited.

    Purpose of the Study:

    • To present a generic framework for comparing vesselness filters.
    • To benchmark seven gold-standard vesselness filters using the proposed framework.
    • To provide an open-source tool for reproducible research and community use.

    Main Methods:

    • Developed a generic framework for vesselness filter comparison.
    • Experimented on three public datasets: hepatic (CT), brain (MRA), and synthetic.
    • Quantitatively and qualitatively analyzed seven filters, focusing on performance across different vessel sizes and bifurcations.

    Main Results:

    • Compared seven vesselness filters on diverse datasets.
    • Assessed filter performance on organ, vascular network, and vessel-specific neighborhoods.
    • Evaluated filter efficacy on vessel bifurcations, often missed in segmentation.

    Conclusions:

    • The benchmark framework facilitates objective comparison of vesselness filters.
    • Results provide insights into filter performance for specific vascular structures and datasets.
    • The provided code and demonstrator support the selection and application of vesselness filters.