Detail publikace

Segmentace cévního řečiště ze snímků sítnice pomocí přizpůsobené filtrace: vyhodnocení na nové databází snímků sítnice s vysokým rozlišením

ODSTRČILÍK, J. KOLÁŘ, R. BUDAI, A. HORNEGGER, J. JAN, J. GAZÁREK, J. KUBĚNA, T. ČERNOŠEK, P. SVOBODA, O. ANGELOPOULOU, E.

Originální název

Retinal Vessel Segmentation by Improved Matched Filtering: Evaluation on a New High–Resolution Fundus Image Database

Český název

Segmentace cévního řečiště ze snímků sítnice pomocí přizpůsobené filtrace: vyhodnocení na nové databází snímků sítnice s vysokým rozlišením

Anglický název

Retinal Vessel Segmentation by Improved Matched Filtering: Evaluation on a New High–Resolution Fundus Image Database

Typ

článek v časopise

Jazyk

en

Originální abstrakt

Automatic assessment of retinal vessels plays an important role in the diagnosis of various eye, as well as systemic diseases. A public screening is highly desirable for prompt and effective treatment, since such diseases need to be diagnosed at an early stage. Automated and accurate segmentation of the retinal blood vessel tree is one of the challenging tasks in the computer-aided analysis of fundus images today. We improve the concept of matched filtering, and propose a novel and accurate method for segmenting retinal vessels. Our goal is to be able to segment blood vessels with varying vessel diameters in high-resolution colour fundus images. All recent authors compare their vessel segmentation results to each other using only low-resolution retinal image databases. Consequently, we provide a new publicly available high-resolution fundus image database of healthy and pathological retinas. Our performance evaluation shows that the proposed blood vessel segmentation approach is at least comparable with recent state-of-the-art methods. It outperforms most of them with an accuracy of 95% evaluated on the new database.

Český abstrakt

Příspěvek se zabývá segmentací cévního řečiště ze snímků sítnice pomocí přizpůsobené filtrace. K vyhodnocení metody byla vytvořena nová veřejná databáze se zlatými standardy.

Anglický abstrakt

Automatic assessment of retinal vessels plays an important role in the diagnosis of various eye, as well as systemic diseases. A public screening is highly desirable for prompt and effective treatment, since such diseases need to be diagnosed at an early stage. Automated and accurate segmentation of the retinal blood vessel tree is one of the challenging tasks in the computer-aided analysis of fundus images today. We improve the concept of matched filtering, and propose a novel and accurate method for segmenting retinal vessels. Our goal is to be able to segment blood vessels with varying vessel diameters in high-resolution colour fundus images. All recent authors compare their vessel segmentation results to each other using only low-resolution retinal image databases. Consequently, we provide a new publicly available high-resolution fundus image database of healthy and pathological retinas. Our performance evaluation shows that the proposed blood vessel segmentation approach is at least comparable with recent state-of-the-art methods. It outperforms most of them with an accuracy of 95% evaluated on the new database.

Klíčová slova

segmentace obrazu, snímky sítnice, přizpůsobená filtrace, segmentace retinálních cév

Rok RIV

2013

Vydáno

16.07.2013

Nakladatel

The Institution of Engineering and Technology

Místo

Stevenage, UK

Strany od

373

Strany do

383

Strany počet

10

URL

BibTex


@article{BUT98394,
  author="Jan {Odstrčilík} and Radim {Kolář} and Attila {Budai} and Joachim {Hornegger} and Jiří {Jan} and Jiří {Gazárek} and Tomáš {Kuběna} and Pavel {Černošek} and Ondřej {Svoboda} and Elli {Angelopoulou}",
  title="Retinal Vessel Segmentation by Improved Matched Filtering: Evaluation on a New High–Resolution Fundus Image Database",
  annote="Automatic assessment of retinal vessels plays an important role in the diagnosis of various eye, as well as systemic diseases. A public screening is highly desirable for prompt and effective treatment, since such diseases need to be diagnosed at an early stage. Automated and accurate segmentation of the retinal blood vessel tree is one of the challenging tasks in the computer-aided analysis of fundus images today. We improve the concept of matched filtering, and propose a novel and accurate method for segmenting retinal vessels. Our goal is to be able to segment blood vessels with varying vessel diameters in high-resolution colour fundus images. All recent authors compare their vessel segmentation results to each other using only low-resolution retinal image databases. Consequently, we provide a new publicly available high-resolution fundus image database of healthy and pathological retinas. Our performance evaluation shows that the proposed blood vessel segmentation approach is at least comparable with recent state-of-the-art methods. It outperforms most of them with an accuracy of 95% evaluated on the new database.",
  address="The Institution of Engineering and Technology",
  chapter="98394",
  doi="10.1049/iet-ipr.2012.0455",
  institution="The Institution of Engineering and Technology",
  number="4",
  volume="7",
  year="2013",
  month="july",
  pages="373--383",
  publisher="The Institution of Engineering and Technology",
  type="journal article"
}