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New diffusion model enables unsupervised segmentation of neonatal brain lesions

Researchers have developed OpenMAP-HIE, a novel diffusion model designed for unsupervised segmentation of neonatal hypoxic-ischemic encephalopathy (HIE) lesions. This pathology-informed model learns healthy brain tissue distributions and uses a ControlNet-based branch to preserve patient anatomy, enabling anomaly detection without direct lesion supervision. Evaluations on the BONBID-HIE dataset showed promising results, with the ADC-only method achieving competitive performance against unsupervised and supervised models, and further refinement improving Dice scores. AI

IMPACT This research could lead to improved diagnostic tools for neonatal brain injuries, potentially aiding in earlier and more accurate treatment.

RANK_REASON The cluster describes a new research paper detailing a novel AI model for medical image segmentation.

Read on Hugging Face Daily Papers →

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New diffusion model enables unsupervised segmentation of neonatal brain lesions

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COVERAGE [2]

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

    OpenMAP-HIE: Pathology Informed Score-based Diffusion Model for Unsupervised Neonatal Hypoxic-Ischemic Encephalopathy Lesion Segmentation

    Accurate localization of neonatal hypoxic--ischemic encephalopathy (HIE) lesions on apparent diffusion coefficient (ADC) images is clinically important but is limited by scarce expert annotations and substantial variation in lesion appearance. We propose OpenMAP-HIE, a pathology-…

  2. arXiv cs.CV TIER_1 English(EN) · Pengyu Kan (Johns Hopkins University), Craig Jones (Johns Hopkins University, University of Alberta), Kenichi Oishi (Johns Hopkins University School of Medicine) ·

    OpenMAP-HIE: Pathology Informed Score-based Diffusion Model for Unsupervised Neonatal Hypoxic-Ischemic Encephalopathy Lesion Segmentation

    arXiv:2610.29322v1 Announce Type: new Abstract: Accurate localization of neonatal hypoxic--ischemic encephalopathy (HIE) lesions on apparent diffusion coefficient (ADC) images is clinically important but is limited by scarce expert annotations and substantial variation in lesion …