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OBBSeg method uses Oriented Bounding Boxes for efficient medical image segmentation · 3 sources tracked

By PulseAugur Editorial · [3 sources] ·

Researchers have developed OBBSeg, a novel method for medical image segmentation that utilizes Oriented Bounding Boxes (OBBs) for intermediate supervision. This approach addresses the bottleneck of pixel-level annotation by providing more precise geometric guidance for elongated or anisotropic lesions than traditional bounding boxes. OBBSeg incorporates a Mask-to-OBB loss to ensure consistency between predicted masks and OBBs, along with prompt-driven semantic guidance modules to improve foreground representation and reduce background noise. Experiments across 13 datasets and 5 imaging modalities demonstrate that OBBSeg achieves performance comparable to fully supervised methods, offering a more efficient and scalable solution for medical image segmentation. AI

IMPACT This method offers a more efficient and scalable approach to medical image segmentation, potentially improving diagnostic accuracy and reducing annotation costs.

RANK_REASON The cluster contains a research paper detailing a new method for medical image segmentation.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

OBBSeg method uses Oriented Bounding Boxes for efficient medical image segmentation · 3 sources tracked

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COVERAGE [3]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    OBBSeg: Irregular Lesion Segmentation under Oriented Bounding Box Annotations

    Pixel-level annotation remains a major bottleneck in medical image segmentation, making weak supervision an attractive yet under-constrained alternative. We propose OBBSeg, an intermediate supervision paradigm guided by Oriented Bounding Boxes (OBBs) that bridges the gap between …

  2. arXiv cs.CV TIER_1 English(EN) · Jun Wei, Xinchang Liu, Yu Liu, Chuhua Yang, Shuhui Wang, Hui Huang ·

    OBBSeg: Irregular Lesion Segmentation under Oriented Bounding Box Annotations

    arXiv:2607.06007v1 Announce Type: new Abstract: Pixel-level annotation remains a major bottleneck in medical image segmentation, making weak supervision an attractive yet under-constrained alternative. We propose OBBSeg, an intermediate supervision paradigm guided by Oriented Bou…

  3. arXiv cs.CV TIER_1 English(EN) · Hui Huang ·

    OBBSeg: Irregular Lesion Segmentation under Oriented Bounding Box Annotations

    Pixel-level annotation remains a major bottleneck in medical image segmentation, making weak supervision an attractive yet under-constrained alternative. We propose OBBSeg, an intermediate supervision paradigm guided by Oriented Bounding Boxes (OBBs) that bridges the gap between …

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