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工業技術研究院

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技術名稱: 糖尿病視網膜病變診斷輔助分析技術

技術簡介

結合醫師專業知識與人工智慧分析之人腦與AI雙腦協作,更有效率協助非眼科醫師進行糖尿病眼底影像的細微病變判讀,加快醫生確診速度 ,免除轉診眼科的不便利,進而提高潛在病患早期發現之比率,早期治療,維護民眾健康,減少醫療照護支出與社會成本。

Abstract

This technology is a collaboration of the minds of the human brain and artificial intelligence through the expertise of doctors and AI analysis. It enhances the efficiency of helping non-ophthalmologist physicians conduct the detection of subtle lesions in fundus images, and eliminates the inconvenience of referrals to ophthalmologists. The technology therefore increases the early detection rate for potential patients and reduces the cost of healthcare and social care.

技術規格

1. 切合台灣糖尿病共同照護網的病變分級需求 - 提供糖尿病視網膜病變五個級別(No DR, Mild NPDR, Moderate NPDR, Severe NPDR, PDR)的分類模型,給予不同分級病患更為貼切的醫療照護。亦提供是否轉診眼科的二分類模型 2. 標示糖尿病視網膜主要病灶的位置 - 國際上目前唯一可偵測四種主要的病徵 (Microaneurysms, Hemorrhages, Soft Exudates, Hard Exudates),並且清楚標示位置的AI判讀技術,可有效輔助醫師針對病變嚴重程度的判讀

Technical Specification

1. Is in accordance with the needs of the severity scales of Taiwan’s Diabetes Shared Care Network - This technology provides a classification model for the five severity scales of diabetic retinopathy (No DR, Mild NPDR, Moderate NPDR, Severe NPDR, PDR), and ensures suitable healthcare for patients with different severity levels. It also produces a binary classification model regarding the decision for referrals to ophthalmologists. 2. Labels the lesion locations of Diabetic Retinopathy - This is currently the only AI detection technology in the world that can detect the main four lesions (Microaneurysms, Hemorrhages, Soft Exudates, Hard Exudates), clearly label the corresponding locations, and effectively assist doctors in the detection of the lesions’ severity levels.

技術特色

.加快醫生確診速度,早期發現治療,維護民眾健康 .結合醫師專業知識與人工智慧分析之人腦與AI雙腦協作,更有效率協助非眼科醫師進行糖尿病眼底影像的細微病變判讀 .免除轉診眼科的不便利,進而提高潛在病患早期發現之比率,減少醫療照護支出與社會成本

應用範圍

糖尿病患者可於新陳代謝科定期回診取藥時,以AI病變嚴重程度分級與病徵辨識輔助非眼科醫師進行眼底影像判讀,達到如眼科專科醫生般的判讀能力,免除轉診眼科的不便利,提升篩檢率。

接受技術者具備基礎建議(設備)

軟體:NVIDIA Container Runtime for Docker、NVIDIA container image of PyTorch、release 17.12。 硬體:至少安裝有一張NVIDIA Pascal以上世代GPU之主機。

接受技術者具備基礎建議(專業)

具機器學習、深度學習、眼底影像分析基本概念。

技術分類 醫學影像分析之機器學習技術與決策支援系統

聯絡資訊

聯絡人:李紀幸 執行長室

電話:+886-3-5917062 或 Email:GraceCHLee@itri.org.tw

客服專線:+886-800-45-8899

傳真:+886-3-5910257

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