血管モデルのテンプレートマッチングによる眼底画像上の主幹動静脈認識精度の改善

概要

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Studies suggest association of retinal microvascular abnormalities with cardiovascular and cerebrovascular diseases. Arteriolar narrowing, which can be assessed by arteriolar-to-venular diameter ratio (AVR) on retinal fundus images, is one of the findings for hypertensive retinopathy. We have been studying an automated method for measuring AVR in hope of improving diagnostic efficiency and consistency of ophthalmologists. One of the problems in our previous method was that the suboptimal segmentation accuracy of the major arteries, especially those with low contrast and central reflex. In order to improve the recognition rate of major vessel pairs, synthetic vessel models were created, and the missed or broken arteries were identified by template matching. The method was applied to 22 retinal fundus images, including cases with arteriolar narrowing. By use of the models with 2 different shape profiles and various sizes, the major vessel recognition rate was improved from 72.7% to 90.9%. The proposed method may be useful in automated measurement of AVR.