Segmentation of macular lesions using active shape contour method

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86099576" target="_blank" >RIV/61989100:27240/16:86099576 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-319-27644-1_20" target="_blank" >http://dx.doi.org/10.1007/978-3-319-27644-1_20</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-27644-1_20" target="_blank" >10.1007/978-3-319-27644-1_20</a>

Result language

angličtina

Original language name

Segmentation of macular lesions using active shape contour method

Original language description

Age-related macular degeneration (ARMD) is one of the most widespread diseases of the eye fundus and is the most common cause of vision loss for those over the age of 60. There are several ways to diagnose ARMD. One of them is the Fundus Autofluorescence (FAF) method, and is one of the modalities of Heidelberg Engineering diagnostic devices. The BluePeakTM modality utilizes the fluorescence of lipofuscin (a pigment in the affected cells) to display the extent of the disease's progression. The native image is further evaluated to more precisely specify the diagnosis of the disease-it is necessary to determine the size of the macular lesion area. Calculations of the geometric parameters of macular lesions were conducted in the MATLAB(R) software; the size of the lesion area was determined using the Image Processing Toolbox. The automated lesion detection method occurs using a parametric active contour (active contours driven by local Gaussian distribution fitting energy) that encloses the affected macular lesion, thereby allowing a precise determination of the affected area. This method is relatively quick for use in clinical practice and allows evaluation the macular lesions exactly based on the proportion with the feature extraction in advance. The proposed methodology is fully automatic. In the algorithm input we define area of interest and initial circle, which is placed inside of the object. Image background issuppressed by low pass filter. Final contour is formed in consecutive steps, up to shape of macular lesion. (C) Springer International Publishing Switzerland 2016.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

JC - Computer hardware and software

OECD FORD branch

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Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2016

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Advances in Intelligent Systems and Computing. Volume 423

ISSN

2194-5357

e-ISSN

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Volume of the periodical

423

Issue of the periodical within the volume

2016

Country of publishing house

CH - SWITZERLAND

Number of pages

9

Pages from-to

213-221

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-84958964415