Comput Methods Programs Biomed - Ultrasound IMT measurement on a multi-ethnic and multi-institutional database: our review and experience using four fully automated and one semi-automated methods.

Tópicos

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Resumo

Automated and high performance carotid intima-media thickness (IMT) measurement is gaining increasing importance in clinical practice to assess the cardiovascular risk of patients. In this paper, we compare four fully automated IMT measurement techniques (CALEX, CAMES, CARES and CAUDLES) and one semi-automated technique (FOAM). We present our experience using these algorithms, whose lumen-intima and media-adventitia border estimation use different methods that can be: (a) edge-based; (b) training-based; (c) feature-based; or (d) directional Edge-Flow based. Our database (DB) consisted of 665 images that represented a multi-ethnic group and was acquired using four OEM scanners. The performance evaluation protocol adopted error measures, reproducibility measures, and Figure of Merit (FoM). FOAM showed the best performance, with an IMT bias equal to 0.025?0.225mm, and a FoM equal to 96.6%. Among the four automated methods, CARES showed the best results with a bias of 0.032?0.279mm, and a FoM to 95.6%, which was statistically comparable to that of FOAM performance in terms of accuracy and reproducibility. This is the first time that completely automated and user-driven techniques have been compared on a multi-ethnic dataset, acquired using multiple original equipment manufacturer (OEM) machines with different gain settings, representing normal and pathologic cases.

Resumo Limpo

autom high perform carotid intimamedia thick imt measur gain increas import clinic practic assess cardiovascular risk patient paper compar four fulli autom imt measur techniqu calex came care caudl one semiautom techniqu foam present experi use algorithm whose lumenintima mediaadventitia border estim use differ method can edgebas b trainingbas c featurebas d direct edgeflow base databas db consist imag repres multiethn group acquir use four oem scanner perform evalu protocol adopt error measur reproduc measur figur merit fom foam show best perform imt bias equal mm fom equal among four autom method care show best result bias mm fom statist compar foam perform term accuraci reproduc first time complet autom userdriven techniqu compar multiethn dataset acquir use multipl origin equip manufactur oem machin differ gain set repres normal patholog case

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