List of Articles STARE

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  1 - Unsupervised Segmentation of Retinal Blood Vessels Using the Human Visual System Line Detection Model
  Mohsen Zardadi Nasser Mehrshad Seyyed Mohammad Razavi
  10.7508/jist.2016.02.008
  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 s More

  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. Manuscript profile
• Open Access Article
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  2 - Retinal Vessel Extraction Using Dynamic Threshold And Enhancement Image Filter From Retina Fundus
  erwin erwin Tomi Kiyatmoko
  10.7508/jist.2018.04.001
  In the diagnosis of retinal disease, Retinal vessels become an important role in determining certain diseases. Retina vessels are an important element with a variety of shapes and sizes, each human blood vessel also can determine the disease with various types, but the More

  In the diagnosis of retinal disease, Retinal vessels become an important role in determining certain diseases. Retina vessels are an important element with a variety of shapes and sizes, each human blood vessel also can determine the disease with various types, but the feasibility of the pattern of retinal blood vessels is very important for the advanced diagnosis process in medical retina such as detection, identification and classification. Improvement and improvement of image quality in this case is very important by focusing on extracting or segmenting the retinal veins so that parameters such as accuracy, specifications, and sensitivity can be obtained that are better and meet the advanced system. Therefore we conducted experiments in order to develop extraction of retinal images to obtain binary images of retinal vessels in the medical world using Dynamic Threshold and Butterworth Bandpass Filter. Using a database DRIVE Accuracy of 94.77%, sensitivity of 54.48% and specificity of 98.71%. Manuscript profile