Retinal Image Enhancement and Automatic Retinal Structure ...



Retinal Image Enhancement and Automatic Retinal Structure Identification

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|Automatic Retinal Vasculature Structure Tracing and Vascular Landmark Extraction from Human Eye Image |

|Eunhwa Jung   Kyungho Hong   |

|Baekseok University, Korea; |

|This paper appears in: Hybrid Information Technology, 2006. ICHIT'06. Vol 2. International Conference on |

|Publication Date: Nov. 2006 |

|Volume: 2,  On page(s): 161-167 |

|Location: Cheju Island, Korea, |

|ISBN: 0-7695-2674-8 |

|Digital Object Identifier: 10.1109/ICHIT.2006.253606 |

|Posted online: 2006-12-11 09:16:15.0 |

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|Abstract |

|We present an effective algorithm for automatic tracing of vasculature structures and vascular landmark extraction of |

|bifurcations and ending points. In this paper we deal with vascular patterns from digital images for personal identification. |

|Vessel tracing algorithms are of interest in a variety of biometric and medical application such as personal identification, |

|biometrics, and ophthalmic disorders like vessel change detection. However eye surface vasculature tracing has many problems |

|which are subject to improper illumination, glare, fade-out, shadow and artifacts arising from reflection, refraction, and |

|dispersion. The proposed algorithm on vascular tracing employs multi-stage processing of ten-layers as followings: Image |

|Acquisition, Image Enhancement by gray scale retinal image enhancement, reducing background artifact and illuminations and |

|removing interlacing minute characteristics of vessels, Vascular Structure Extraction by connecting broken vessels, extracting |

|vascular structure using eight directional information, and extracting retinal vascular structure. Vascular Landmark Extraction |

|of bifurcations and ending points. The results of automatic retinal vessel extraction using five different thresholds applied 34|

|eye images are presented. The results of vasculature tracing algorithm shows that the suggested algorithm can obtain not only |

|robust and accurate vessel tracing but also vascular landmarks according to thresholds. |



|Automatic Detection of Microaneurysms in Color Fundus Images of the Human Retina by Means of the Bounding Box |Add to marked items|

|Closing | |

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|Lecture Notes in Computer Science |cart |

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|Publisher |Recommend this |

|Springer Berlin / Heidelberg |chapter |

| | |

|ISSN | |

|0302-9743 | |

| | |

|Subject | |

|Computer Science | |

| | |

|Volume | |

|Volume 2526/2002 | |

| | |

|Book | |

|Medical Data Analysis Third International : Third International Symposium, ISMDA 2002 Rome, Italy, October | |

|10-11, 2002. Proceedings | |

| | |

|Copyright | |

|2002 | |

| | |

|Pages | |

|210-220 | |

| | |

|SpringerLink Date | |

|Thursday, February 19, 2004 | |

| | |

|Authors |

|Thomas Walter, Jean-Claude Klein |

|Abstract |

|In this paper we propose a new algorithm for the detection of microaneurysms in|

|color fundus images of the human retina. Microaneurysms are the first |

|unequivocal indication of Diabetic Retinopathy (DR), a severe and wide-spread |

|eye disease. Their automatic detection may play a major role in computer |

|assisted diagnosis of DR. We propose an algorithm that can be divided into four|

|steps. The first step is an image enhancement technique that comprises |

|normalization and noise reduction. The second step ist the extraction of small |

|details that fulfill a certain criterion: This leads to the definition of the |

|bounding box closing. Then, an automatic threshold depending on image quality |

|is calculated. In the last step false positives are eliminated. |



OptiScan, Digiscope, etc.:

Digital Retinal Imaging and the New Era of Ophthalmic Telemedicine



Enhancing Ophthalmic Digital Images



Adaptive image enhancement for retinal blood vessel segmentation ...

|File Format: PDF/Adobe Acrobat |

|534-537. 1anuaty 2002. Adaptive image enhancement for retinal. blood vessel segmentation. Tusheng. Lin. and Yibin Zheng. |

|Retinal blood. vessel. images ... |

|ieeexplore.iel5/2220/22262/01038607.pdf?arnumber=1038607 |



ScienceDirect - Ophthalmology : Visualization of localized retinal ...

|Visualization of localized retinal nerve fiber layer defects with the GDx with ... and the striation of the RNFL with |

|standard image enhancement techniques. ... |

|linkinghub.retrieve/pii/S0161642003004792 |



|Retinal image enhancement based on the human |

|visual system |

|Authors: | |Belkacem-Boussaid, Kamel; Raman, Balaji; Zamora, Gilberto; Srinivasan, Yeshwanth;|

| | |Bursell, Sven-Erick |

Abstract

Improving the quality of gray level images continues to be a challenging task, and the challenge increases for color images due to the interaction of multiple parameters within a scene. Each color plane or wavelength constitutes an image by itself, and its quality depends on many parameters such as absorption, reflectance or scattering of the object with the lighting source. Non-uniformity of the lighting, optics, electronics of the camera, and even the environment of the object are sources of degradation in the image. Therefore, segmentation and interpretation of the image may become very difficult if its quality is not enhanced. The main goal of the present work is to demonstrate image processing algorithm that is inspired from some concepts of the Human Visual System (HVS). HVS concepts have been widely used in gray level image enhancement and here we show how they can be successfully extended to color images. The resulting Multi-Scale Spatial Decomposition (MSSD) is employed to enhance the quality of color images. Of particular interest for medical imaging is the enhancement of retinal images whose quality is extremely sensitive to imaging artifacts. We show that our MSSD algorithm improves the readability and gradeability of retinal images and quantify such improvements using both subjective and objective metrics of image quality.

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