使用Hölder指数自动图像评估后囊膜混浊

2013 IEEE 20th International Conference on Electronics, Circuits, and Systems (ICECS) Pub Date : 2013-12-01 DOI:10.1109/ICECS.2013.6815470

A. Vivekanand, N. Werghi, H. Al-Ahmad

{"title":"使用Hölder指数自动图像评估后囊膜混浊","authors":"A. Vivekanand, N. Werghi, H. Al-Ahmad","doi":"10.1109/ICECS.2013.6815470","DOIUrl":null,"url":null,"abstract":"Posterior Capsule Opacification (PCO) remains to be the most common complication of cataract surgery after intraocular lens implantation. Though several strategies have been suggested for the prevention of PCO, a standard PCO quantification system is required to reliably assess the effectiveness of these strategies. This paper proposes a method based on computation of Hölder exponents to quantify the amount of PCO in the digital image. PCO areas are effectively detected and classified according to their severity using histogram-based thresholding on Hölder exponent image. This method is implemented in Matlab and verified on real PCO images. The results show a high correlation of 83% between the computed PCO scores and the clinical grades, as well as demonstrate the robustness of the proposed system to monotonic illumination variations.","PeriodicalId":117453,"journal":{"name":"2013 IEEE 20th International Conference on Electronics, Circuits, and Systems (ICECS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Automated image assessment of posterior capsule opacification using Hölder exponents\",\"authors\":\"A. Vivekanand, N. Werghi, H. Al-Ahmad\",\"doi\":\"10.1109/ICECS.2013.6815470\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Posterior Capsule Opacification (PCO) remains to be the most common complication of cataract surgery after intraocular lens implantation. Though several strategies have been suggested for the prevention of PCO, a standard PCO quantification system is required to reliably assess the effectiveness of these strategies. This paper proposes a method based on computation of Hölder exponents to quantify the amount of PCO in the digital image. PCO areas are effectively detected and classified according to their severity using histogram-based thresholding on Hölder exponent image. This method is implemented in Matlab and verified on real PCO images. The results show a high correlation of 83% between the computed PCO scores and the clinical grades, as well as demonstrate the robustness of the proposed system to monotonic illumination variations.\",\"PeriodicalId\":117453,\"journal\":{\"name\":\"2013 IEEE 20th International Conference on Electronics, Circuits, and Systems (ICECS)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE 20th International Conference on Electronics, Circuits, and Systems (ICECS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICECS.2013.6815470\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 20th International Conference on Electronics, Circuits, and Systems (ICECS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECS.2013.6815470","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 2

摘要

摘要后囊膜混浊是人工晶状体植入术后白内障手术最常见的并发症。虽然已经提出了几种预防PCO的策略，但需要一个标准的PCO量化系统来可靠地评估这些策略的有效性。本文提出了一种基于Hölder指数计算的数字图像中PCO量的量化方法。对Hölder指数图像采用基于直方图的阈值分割方法，有效地检测和分类PCO区域的严重程度。该方法在Matlab中实现，并在实际PCO图像上进行了验证。结果表明，计算得到的PCO分数与临床评分之间的相关性高达83%，并证明了所提出的系统对单调光照变化的鲁棒性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Automated image assessment of posterior capsule opacification using Hölder exponents

Posterior Capsule Opacification (PCO) remains to be the most common complication of cataract surgery after intraocular lens implantation. Though several strategies have been suggested for the prevention of PCO, a standard PCO quantification system is required to reliably assess the effectiveness of these strategies. This paper proposes a method based on computation of Hölder exponents to quantify the amount of PCO in the digital image. PCO areas are effectively detected and classified according to their severity using histogram-based thresholding on Hölder exponent image. This method is implemented in Matlab and verified on real PCO images. The results show a high correlation of 83% between the computed PCO scores and the clinical grades, as well as demonstrate the robustness of the proposed system to monotonic illumination variations.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2013 IEEE 20th International Conference on Electronics, Circuits, and Systems (ICECS)

自引率

0.00%

发文量