Modeling and extraction of retinal blood vessels from RetCam 3 based on morphological segmentation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F20%3A10244961" target="_blank" >RIV/61989100:27240/20:10244961 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00843989:_____/20:E0107986

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-030-14132-5_20" target="_blank" >http://dx.doi.org/10.1007/978-3-030-14132-5_20</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-14132-5_20" target="_blank" >10.1007/978-3-030-14132-5_20</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Modeling and extraction of retinal blood vessels from RetCam 3 based on morphological segmentation

Popis výsledku v původním jazyce

This paper deals with the analysis and modeling of the retinal blood vessels system. The aim of the analysis is the design and implementation of a fully automated segmentation model based on the morphological segmentation, allowing for extraction of the blood system area within the binary model, where other retinal structures are suppressed. An important feature of the model is sensitivity and robustness to declare the efficacy of segmentation in an environment with worse image parameters. For this reason, the designed model is also tested for data where the vascular system is visualized under a low contrast. Part of the analysis is the comparative testing of the designed model against selected segmentation methods based on objective criteria. The designed model was tested and verified on dataset from system RetCam 3 containing 22 images. (C) Springer Nature Switzerland AG 2020.

Název v anglickém jazyce

Modeling and extraction of retinal blood vessels from RetCam 3 based on morphological segmentation

Popis výsledku anglicky

This paper deals with the analysis and modeling of the retinal blood vessels system. The aim of the analysis is the design and implementation of a fully automated segmentation model based on the morphological segmentation, allowing for extraction of the blood system area within the binary model, where other retinal structures are suppressed. An important feature of the model is sensitivity and robustness to declare the efficacy of segmentation in an environment with worse image parameters. For this reason, the designed model is also tested for data where the vascular system is visualized under a low contrast. Part of the analysis is the comparative testing of the designed model against selected segmentation methods based on objective criteria. The designed model was tested and verified on dataset from system RetCam 3 containing 22 images. (C) Springer Nature Switzerland AG 2020.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

10200 - Computer and information sciences

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název knihy nebo sborníku

Studies in Computational Intelligence. Volume 830

ISBN

978-3-030-14131-8

Počet stran výsledku

9

Strana od-do

255-263

Počet stran knihy

9

Název nakladatele

Springer

Místo vydání

Cham

Kód UT WoS kapitoly

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