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BifDet dataset released for 3D airway bifurcation detection in CT scans

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced BifDet, a new dataset designed for detecting 3D airway bifurcations in CT scans. This dataset addresses a significant gap in resources for analyzing lung physiology and disease mechanisms. BifDet includes annotated CT scans from the ATM22 cohort, with bounding boxes for parent and daughter airway branches. The paper also demonstrates the dataset's utility by fine-tuning and evaluating RetinaNet and DETR models for bifurcation detection, providing baseline results for future research. AI

IMPACT Provides a specialized dataset for advancing AI-driven analysis of respiratory diseases through airway tree modeling.

RANK_REASON The cluster describes the release of a new dataset and associated research paper on arXiv.

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

BifDet dataset released for 3D airway bifurcation detection in CT scans

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COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Ali Keshavarzi, Quentin Bouniot, Benjamin M. Smith, Elsa Angelini ·

    BifDet: A 3D Bifurcation Detection Dataset for Airway-Tree Modeling

    arXiv:2604.24999v1 Announce Type: new Abstract: Thoracic Computed Tomography (CT) scans offer detailed insights into the intricate branching network of the airway tree, which is essential for understanding various respiratory diseases. Airway bifurcations, where airway branches s…

  2. arXiv cs.CV TIER_1 English(EN) · Elsa Angelini ·

    BifDet: A 3D Bifurcation Detection Dataset for Airway-Tree Modeling

    Thoracic Computed Tomography (CT) scans offer detailed insights into the intricate branching network of the airway tree, which is essential for understanding various respiratory diseases. Airway bifurcations, where airway branches split, are crucial landmarks for understanding lu…

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