医用画像情報学会雑誌
Online ISSN : 1880-4977
Print ISSN : 0910-1543
ISSN-L : 0910-1543
論文
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
村松 千左子水上 篤貴畑中 裕司澤田 明原 武史山本 哲也藤田 広志
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2013 年 30 巻 3 号 p. 63-69

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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.

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© 2013 医用画像情報学会
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