Computer-aided diagnostic detection system of venous beading in retinal images

Ching Wen Yang; Dye Jyun Ma; Shuenn Ching Chao; Chuin Mu Wang; Chia Hsin Wen; Chien Shun Lo; Pau Choo Chung; Chein I. Chang

doi:10.1117/1.602487

Computer-aided diagnostic detection system of venous beading in retinal images

Ching Wen Yang, Dye Jyun Ma, Shuenn Ching Chao, Chuin Mu Wang, Chia Hsin Wen, Chien Shun Lo, Pau Choo Chung, Chein I. Chang

Department of Electrical Engineering

Research output: Contribution to journal › Article › peer-review

15 Citations (Scopus)

Abstract

The detection of venous beading in retinal images provides an early sign of diabetic retinopathy and plays an important role as a preprocessing step in diagnosing ocular diseases. We present a computer-aided diagnostic system to automatically detect venous beading of blood vessels. It comprises of two modules, referred to as the blood vessel extraction module (BVEM) and the venus beading detection module (VBDM). The former uses a bell-shaped Gaussian kernel with 12 azimuths to extract blood vessels while the latter applies a neural network-based shape cognitron to detect venous beading among the extracted blood vessels for diagnosis. Both modules are fully computer-automated. To evaluate the proposed system, 61 retinal images (32 beaded and 29 normal images) are used for performance evaluation.

Original language	English
Pages (from-to)	1293-1303
Number of pages	11
Journal	Optical Engineering
Volume	39
Issue number	5
DOIs	https://doi.org/10.1117/1.602487
Publication status	Published - 2000

All Science Journal Classification (ASJC) codes

Atomic and Molecular Physics, and Optics
General Engineering

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10.1117/1.602487

Cite this

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abstract = "The detection of venous beading in retinal images provides an early sign of diabetic retinopathy and plays an important role as a preprocessing step in diagnosing ocular diseases. We present a computer-aided diagnostic system to automatically detect venous beading of blood vessels. It comprises of two modules, referred to as the blood vessel extraction module (BVEM) and the venus beading detection module (VBDM). The former uses a bell-shaped Gaussian kernel with 12 azimuths to extract blood vessels while the latter applies a neural network-based shape cognitron to detect venous beading among the extracted blood vessels for diagnosis. Both modules are fully computer-automated. To evaluate the proposed system, 61 retinal images (32 beaded and 29 normal images) are used for performance evaluation.",

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AU - Yang, Ching Wen

AU - Ma, Dye Jyun

AU - Chao, Shuenn Ching

AU - Wang, Chuin Mu

AU - Wen, Chia Hsin

AU - Lo, Chien Shun

AU - Chung, Pau Choo

AU - Chang, Chein I.

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AB - The detection of venous beading in retinal images provides an early sign of diabetic retinopathy and plays an important role as a preprocessing step in diagnosing ocular diseases. We present a computer-aided diagnostic system to automatically detect venous beading of blood vessels. It comprises of two modules, referred to as the blood vessel extraction module (BVEM) and the venus beading detection module (VBDM). The former uses a bell-shaped Gaussian kernel with 12 azimuths to extract blood vessels while the latter applies a neural network-based shape cognitron to detect venous beading among the extracted blood vessels for diagnosis. Both modules are fully computer-automated. To evaluate the proposed system, 61 retinal images (32 beaded and 29 normal images) are used for performance evaluation.

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Computer-aided diagnostic detection system of venous beading in retinal images

Abstract

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