Optic disc boundary and vessel origin

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Engineering

Logic Mind Technologies
Vijayangar (Near Maruthi Medicals), Bangalore-40
Ph: 8123668124 // 8123668066
Title: Optic Disc Boundary and Vessel Origin
Segmentation of Fundus Images
Abstract—This paperpresents a novel classification-based opticdisc (OD)
segmentation algorithm that detects the OD boundary and the location of
vessel origin (VO) pixel. First, the green plane of each fundus image is
resized and morphologically reconstructed using a circular structuring
element. Bright regions are then extracted from the morphologically
reconstructed image that lie in close vicinity of the major blood vessels.
Next, the bright regions are classified as bright probable OD regions
andnon-OD regions using 6 region-based features and a GaussianMixture
Model classifier. The classified bright probable ODregion with maximum
Vessel-Sum and Solidity is detected as the best candidate region for the
OD. Other bright probable OD regions within 1-disc diameter from the
centroid of the best candidate OD region are then detected as remaining
candidate regions for the OD. A convex hull containing all the candidate
ODregions is then estimated, and a best-fit ellipse across the convexhull
becomes the segmented OD boundary. Finally, the centroidof major blood
vessels within the segmented OD boundary is detected as the VO pixel
location. The proposed algorithm has low computation
timecomplexityanditisrobusttovariations in image illumination, imaging
angles and retinal abnormalities. This algorithm achieves 98.8-100% OD
segmentation success and OD segmentation overlap score in the range of
72-84% on images from the 6 public data sets of DRIVE, DIARETDB1,
DIARETDB0, CHASE DB1, MESSIDOR and STARE in less than 2.14
seconds per image. Thus, the proposed algorithm can be used for
automated detection of retinal pathologies such as glaucoma, diabetic
retinopathy and maculopathy.

Software & Hardware requirement:
1. Hardware requirement:
1. PC
2. RAM minimum 2GB
3. HDD minimum 100GB
2. Software requirement:
1. MATLAB 7.0
2. Signal processing toolbox
3. Image processing toolbox
4. Mathematical toolbox
PROJECT FLOW:
First Review:
Literature Survey
Paper Explanation
Design of Project
Project Enhancement explanation
Second Review:
Implementing 40% of Base Paper
Third Review
Implementing Remaining 60% of Base Paper with Future Enhancement
(Modification)
For More Details please contact
Logic Mind Technologies
Vijayangar (Near Maruthi Medicals), Bangalore-40
Ph: 8123668124 // 8123668066

 Teamed with 2 students to research and implement the automation of diagnosis of Diabetic Retinopathy and co-ordinated with an Ophthalmologist to verify our implementation.  Responsibilities included MATLAB coding, algorithm testing, and product documentation. • Automation in MATLAB involving retinal image analysis to help Ophthalmologist increase the productivity and efficiency in a clinical environment. • Used Image Processing concepts such as Hough Transform, Bottom Hat Transform, Edge Detection Technique and Morphological Operators.  Provided our algorithm and documentation to our research faculty advisor to enable him to continue this research to the next phase.

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The retinal image diagnosis is an important methodology for diabetic retinopathy detection and analysis. in this paper, the morphological operations and svm classifier are used to detect and segment the blood vessels from the retinal image. the proposed system consists of three stage s - first is preprocessing of retinal image to separate the green channel and second stage is retinal image enhancement and third stage is blood vessel segmentation using morphological operations and svm classifier. the performance of the proposed system is analyzed using publicly available dataset

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George Azzopardi, Nicola Strisciuglio, Mario Vento, Nicolai Petkov - "Trainable COSFIRE filters for vessel delineation with application to retinal images”, Medical Image Analysis, Available Online 3 September 2014, DOI: 10.1016/j.media.2014.08.002 The source code of the B-COSFIRE filters is available at: http://www.mathworks.com/matlabcentral/fileexchange/49172-trainable-cosfire-filters-for-vessel-delineation-with-application-to-retinal-images

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Retinal image analysis is increasingly prominent as a non-intrusive diagnosis method in modern ophthalmology. In this paper, we present a novel method to segment blood vessels and optic disc in the fundus retinal images. The method could be used to support non-intrusive diagnosis in modern ophthalmology since the morphology of the blood vessel and the optic disc is an important indicator for diseases like diabetic retinopathy, glaucoma and hypertension. Our method takes as first step the extraction of the retina vascular tree using the graph cut technique. The blood vessel information is then used to estimate the location of the optic disc. The optic disc segmentation is performed using two alternative methods. The Markov Random Field (MRF) image reconstruction method segments the optic disc by removing vessels from the optic disc region and the Compensation Factor method segments the optic disc using prior local intensity knowledge of the vessels. The proposed method is tested on three public data sets, DIARETDB1, DRIVE and STARE. The results and comparison with alternative methods show that our method achieved exceptional performance in segmenting the blood vessel and optic disc.

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IIT毕业证原版定制【微信：176555708】【伊利诺伊理工大学毕业证成绩单-学位证】【微信：176555708】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。 ◆◆◆◆◆ — — — — — — — — 【留学教育】留学归国服务中心 — — — — — -◆◆◆◆◆ 【主营项目】一.毕业证【微信：176555708】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！二.真实使馆公证(即留学回国人员证明,不成功不收费) 三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度) 如果您处于以下几种情况： ◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【微信：176555708】 ◇面对父母的压力，希望尽快拿到； ◇不清楚认证流程以及材料该如何准备； ◇回国时间很长，忘记办理； ◇回国马上就要找工作，办给用人单位看； ◇企事业单位必须要求办理的 ◇需要报考公务员、购买免税车、落转户口 ◇申请留学生创业基金留信网认证的作用: 1:该专业认证可证明留学生真实身份 2:同时对留学生所学专业登记给予评定 3:国家专业人才认证中心颁发入库证书 4:这个认证书并且可以归档倒地方 5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息 6:个人职称评审加20分 7:个人信誉贷款加10分→ 【关于价格问题（保证一手价格）我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子我给客户的都是第一手的代理价格，因为我想坦诚对待大家不想跟大家在价格方面浪费时间对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。 8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！学历顾问：微信：176555708

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ydteq

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Optic disc boundary and vessel origin

1. Logic Mind Technologies Vijayangar (Near Maruthi Medicals), Bangalore-40 Ph: 8123668124 // 8123668066 Title: Optic Disc Boundary and Vessel Origin Segmentation of Fundus Images Abstract—This paperpresents a novel classification-based opticdisc (OD) segmentation algorithm that detects the OD boundary and the location of vessel origin (VO) pixel. First, the green plane of each fundus image is resized and morphologically reconstructed using a circular structuring element. Bright regions are then extracted from the morphologically reconstructed image that lie in close vicinity of the major blood vessels. Next, the bright regions are classified as bright probable OD regions andnon-OD regions using 6 region-based features and a GaussianMixture Model classifier. The classified bright probable ODregion with maximum Vessel-Sum and Solidity is detected as the best candidate region for the OD. Other bright probable OD regions within 1-disc diameter from the centroid of the best candidate OD region are then detected as remaining candidate regions for the OD. A convex hull containing all the candidate ODregions is then estimated, and a best-fit ellipse across the convexhull becomes the segmented OD boundary. Finally, the centroidof major blood vessels within the segmented OD boundary is detected as the VO pixel location. The proposed algorithm has low computation timecomplexityanditisrobusttovariations in image illumination, imaging angles and retinal abnormalities. This algorithm achieves 98.8-100% OD segmentation success and OD segmentation overlap score in the range of 72-84% on images from the 6 public data sets of DRIVE, DIARETDB1, DIARETDB0, CHASE DB1, MESSIDOR and STARE in less than 2.14 seconds per image. Thus, the proposed algorithm can be used for automated detection of retinal pathologies such as glaucoma, diabetic retinopathy and maculopathy.

2. Software & Hardware requirement: 1. Hardware requirement: 1. PC 2. RAM minimum 2GB 3. HDD minimum 100GB 2. Software requirement: 1. MATLAB 7.0 2. Signal processing toolbox 3. Image processing toolbox 4. Mathematical toolbox PROJECT FLOW: First Review: Literature Survey Paper Explanation Design of Project Project Enhancement explanation Second Review: Implementing 40% of Base Paper Third Review Implementing Remaining 60% of Base Paper with Future Enhancement (Modification) For More Details please contact Logic Mind Technologies Vijayangar (Near Maruthi Medicals), Bangalore-40 Ph: 8123668124 // 8123668066

3. Mail: logicmindtech@gmail.com

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