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New HD-DinoMoE network aids scleral anomaly segmentation

Researchers have developed HD-DinoMoE, a novel network designed for segmenting scleral anomalies in ocular inspection images. This system aims to bring objectivity and quantification to Traditional Chinese Medicine's empirical ocular diagnostics. The network utilizes a class-aware hierarchical dual mixture-of-experts approach to handle variations in image acquisition, anomaly types, and specular reflections, achieving competitive segmentation performance on a new benchmark dataset. AI

IMPACT This research offers a more objective and quantifiable approach to ocular diagnostics, potentially improving the accuracy and consistency of scleral anomaly detection.

RANK_REASON The cluster contains a research paper detailing a new model and dataset for a specific computer vision task.

Read on arXiv cs.CV →

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

New HD-DinoMoE network aids scleral anomaly segmentation

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COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Yinxiang Yu, Maoxiang Chu, Qi Niu, Guanghu Liu, Wei Xu, Haotian Wang, Zhi Chen, Yutian Zhu, Yuelong Fan, Guanghao Liao ·

    HD-DinoMoE: A Class-Aware Hierarchical Dual Mixture-of-Experts Network for Scleral Anomaly Segmentation in Complex Acquisition Scenarios

    arXiv:2606.04888v1 Announce Type: new Abstract: Traditional Chinese Medicine (TCM) ocular inspection provides empirical cues for assessing scleral surface anomalies, but its clinical use remains subjective and difficult to quantify. To support intelligent and quantifiable ocular …

  2. arXiv cs.CV TIER_1 English(EN) · Guanghao Liao ·

    HD-DinoMoE: A Class-Aware Hierarchical Dual Mixture-of-Experts Network for Scleral Anomaly Segmentation in Complex Acquisition Scenarios

    Traditional Chinese Medicine (TCM) ocular inspection provides empirical cues for assessing scleral surface anomalies, but its clinical use remains subjective and difficult to quantify. To support intelligent and quantifiable ocular inspection, this study presents the TCM-inspired…