An Automatic Image Processing System for Glaucoma Screening.

IF 3.3 Q2 ENGINEERING, BIOMEDICAL

International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-08-29 DOI:10.1155/2017/4826385

Ahmed Almazroa, Sami Alodhayb, Kaamran Raahemifar, Vasudevan Lakshminarayanan

{"title":"An Automatic Image Processing System for Glaucoma Screening.","authors":"Ahmed Almazroa, Sami Alodhayb, Kaamran Raahemifar, Vasudevan Lakshminarayanan","doi":"10.1155/2017/4826385","DOIUrl":null,"url":null,"abstract":"<p><p>Horizontal and vertical cup to disc ratios are the most crucial parameters used clinically to detect glaucoma or monitor its progress and are manually evaluated from retinal fundus images of the optic nerve head. Due to the rarity of the glaucoma experts as well as the increasing in glaucoma's population, an automatically calculated horizontal and vertical cup to disc ratios (HCDR and VCDR, resp.) can be useful for glaucoma screening. We report on two algorithms to calculate the HCDR and VCDR. In the algorithms, level set and inpainting techniques were developed for segmenting the disc, while thresholding using Type-II fuzzy approach was developed for segmenting the cup. The results from the algorithms were verified using the manual markings of images from a dataset of glaucomatous images (retinal fundus images for glaucoma analysis (RIGA dataset)) by six ophthalmologists. The algorithm's accuracy for HCDR and VCDR combined was 74.2%. Only the accuracy of manual markings by one ophthalmologist was higher than the algorithm's accuracy. The algorithm's best agreement was with markings by ophthalmologist number 1 in 230 images (41.8%) of the total tested images.</p>","PeriodicalId":47063,"journal":{"name":"International Journal of Biomedical Imaging","volume":"2017 ","pages":"4826385"},"PeriodicalIF":3.3000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2017/4826385","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Biomedical Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2017/4826385","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2017/8/29 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}

引用次数: 26

Abstract

Horizontal and vertical cup to disc ratios are the most crucial parameters used clinically to detect glaucoma or monitor its progress and are manually evaluated from retinal fundus images of the optic nerve head. Due to the rarity of the glaucoma experts as well as the increasing in glaucoma's population, an automatically calculated horizontal and vertical cup to disc ratios (HCDR and VCDR, resp.) can be useful for glaucoma screening. We report on two algorithms to calculate the HCDR and VCDR. In the algorithms, level set and inpainting techniques were developed for segmenting the disc, while thresholding using Type-II fuzzy approach was developed for segmenting the cup. The results from the algorithms were verified using the manual markings of images from a dataset of glaucomatous images (retinal fundus images for glaucoma analysis (RIGA dataset)) by six ophthalmologists. The algorithm's accuracy for HCDR and VCDR combined was 74.2%. Only the accuracy of manual markings by one ophthalmologist was higher than the algorithm's accuracy. The algorithm's best agreement was with markings by ophthalmologist number 1 in 230 images (41.8%) of the total tested images.

Abstract Image

查看原文本刊更多论文

青光眼筛查的自动图像处理系统。

水平和垂直杯盘比是临床上用于检测青光眼或监测其进展的最重要参数，并通过视神经头的视网膜眼底图像进行人工评估。由于青光眼专家的稀少和青光眼人群的增加，自动计算水平和垂直杯盘比(HCDR和VCDR，分别)可用于青光眼筛查。我们报告了计算HCDR和VCDR的两种算法。在算法中，开发了水平集和图像绘制技术用于分割椎间盘，而使用ii型模糊方法的阈值法用于分割杯子。六位眼科医生使用青光眼图像数据集(用于青光眼分析的视网膜眼底图像(RIGA数据集))的图像手工标记来验证算法的结果。该算法对HCDR和VCDR的综合准确率为74.2%。只有一位眼科医生手工标记的准确性高于该算法的准确性。该算法在230张(41.8%)测试图像中与1号眼科医生的标记最吻合。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

International Journal of Biomedical Imaging ENGINEERING, BIOMEDICAL-

CiteScore

12.00

自引率

0.00%

发文量

审稿时长

20 weeks

期刊介绍： The International Journal of Biomedical Imaging is managed by a board of editors comprising internationally renowned active researchers. The journal is freely accessible online and also offered for purchase in print format. It employs a web-based review system to ensure swift turnaround times while maintaining high standards. In addition to regular issues, special issues are organized by guest editors. The subject areas covered include (but are not limited to): Digital radiography and tomosynthesis X-ray computed tomography (CT) Magnetic resonance imaging (MRI) Single photon emission computed tomography (SPECT) Positron emission tomography (PET) Ultrasound imaging Diffuse optical tomography, coherence, fluorescence, bioluminescence tomography, impedance tomography Neutron imaging for biomedical applications Magnetic and optical spectroscopy, and optical biopsy Optical, electron, scanning tunneling/atomic force microscopy Small animal imaging Functional, cellular, and molecular imaging Imaging assays for screening and molecular analysis Microarray image analysis and bioinformatics Emerging biomedical imaging techniques Imaging modality fusion Biomedical imaging instrumentation Biomedical image processing, pattern recognition, and analysis Biomedical image visualization, compression, transmission, and storage Imaging and modeling related to systems biology and systems biomedicine Applied mathematics, applied physics, and chemistry related to biomedical imaging Grid-enabling technology for biomedical imaging and informatics