UNSUPERVISED SEGMENTATION OF RETINAL BLOOD VESSELS USING THE HUMAN VISUAL SYSTEM LINE DETECTION MODEL

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ZARDADI MOHSEN; MEHRSHAD NASSER; RAZAVI SEYYED MOHAMMAD

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Paper Information

Journal: Journal of Information Systems and Telecommunication Year:2016 | Volume:4 | Issue:2 Page(s): 125-133

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Title

UNSUPERVISED SEGMENTATION OF RETINAL BLOOD VESSELS USING THE HUMAN VISUAL SYSTEM LINE DETECTION MODEL

Author(s)

ZARDADI MOHSEN | MEHRSHAD NASSER | RAZAVI SEYYED MOHAMMAD | Issue Writer Certificate

Keywords

RETINAL VESSEL SEGMENTATION

SIMPLE CELL MODEL

DRIVE DATABASE

STARE DATABASE

Abstract

Retinal image assessment has been employed by the medical community for diagnosing vascular and non-vascular pathology. Computer based analysis of blood vessels in retinal images will help ophthalmologists monitor larger populations for vessel abnormalities. Automatic segmentation of blood vessels from retinal images is the initial step of the computer based assessment for blood vessel anomalies. In this paper, a fast unsupervised method for automatic detection of blood vessels in retinal images is presented. In order to eliminate optic disc and background noise in the fundus images, a simple preprocessing technique is introduced. First, a newly devised method, based on a SIMPLE CELL MODEL of the human visual system (HVS) enhances the blood vessels in various directions. Then, an activity function is presented on simple cell responses. Next, an adaptive threshold is used as an unsupervised classifier and classifies each pixel as a vessel pixel or a non-vessel pixel to obtain a vessel binary image. Lastly, morphological post-processing is applied to eliminate exudates which are detected as blood vessels. The method was tested on two publicly available databases, DRIVE and STARE, which are frequently used for this purpose. The results demonstrate that the performance of the proposed algorithm is comparable with state-of-the-art techniques.

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APA: Copy

ZARDADI, MOHSEN, MEHRSHAD, NASSER, & RAZAVI, SEYYED MOHAMMAD. (2016). UNSUPERVISED SEGMENTATION OF RETINAL BLOOD VESSELS USING THE HUMAN VISUAL SYSTEM LINE DETECTION MODEL. JOURNAL OF INFORMATION SYSTEMS AND TELECOMMUNICATION (JIST), 4(2), 125-133. SID. https://sid.ir/paper/332708/en

Vancouver: Copy

ZARDADI MOHSEN, MEHRSHAD NASSER, RAZAVI SEYYED MOHAMMAD. UNSUPERVISED SEGMENTATION OF RETINAL BLOOD VESSELS USING THE HUMAN VISUAL SYSTEM LINE DETECTION MODEL. JOURNAL OF INFORMATION SYSTEMS AND TELECOMMUNICATION (JIST)[Internet]. 2016;4(2):125-133. Available from: https://sid.ir/paper/332708/en

IEEE: Copy

MOHSEN ZARDADI, NASSER MEHRSHAD, and SEYYED MOHAMMAD RAZAVI, “UNSUPERVISED SEGMENTATION OF RETINAL BLOOD VESSELS USING THE HUMAN VISUAL SYSTEM LINE DETECTION MODEL,” JOURNAL OF INFORMATION SYSTEMS AND TELECOMMUNICATION (JIST), vol. 4, no. 2, pp. 125–133, 2016, [Online]. Available: https://sid.ir/paper/332708/en

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