Robust Automatic Montaging of Adaptive Optics Flood Illumination Retinal Images

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F21%3APU141401" target="_blank" >RIV/00216305:26220/21:PU141401 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1007/978-3-030-80432-9_37" target="_blank" >https://doi.org/10.1007/978-3-030-80432-9_37</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-80432-9_37" target="_blank" >10.1007/978-3-030-80432-9_37</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Robust Automatic Montaging of Adaptive Optics Flood Illumination Retinal Images

Popis výsledku v původním jazyce

Adaptive optics (AO) flood illumination camera acquires retinal images with a limited field of view, which can be extended by image alignment into one wide field of view montage image. The image alignment into a montage requires efficient and accurate image registration. Since manual registration is demanding and disadvantageous, automatic registration is a beneficial improvement. We propose the first fully automated AO retinal image montage procedure. Here, we present three novel fully automated registration methods, which are based on two established image processing approaches. The first method utilizes scale invariant feature transform (SIFT) in combination with specific image preprocessing. The second method uses the phase correlation (PC) approach and the last method is a connection of PC and SIFT (PC-SIFT) algorithm. In total, 200 images acquired from the left and right eyes of 10 subjects were used for creating the wide field-of-view montage images and compared with manual montaging. The automated image montage was successfully achieved. Alignment accuracy evaluated by normalized mutual information metric showed that the PC-SIFT approach established the most accurate results, these are higher than manual montaging. Therefore, the AO montaging registration methods are able to achieve promising results in accuracy and time demand in comparison with manual montaging. Hence, the latter can be replaced by those fully automated procedures.

Název v anglickém jazyce

Robust Automatic Montaging of Adaptive Optics Flood Illumination Retinal Images

Popis výsledku anglicky

Adaptive optics (AO) flood illumination camera acquires retinal images with a limited field of view, which can be extended by image alignment into one wide field of view montage image. The image alignment into a montage requires efficient and accurate image registration. Since manual registration is demanding and disadvantageous, automatic registration is a beneficial improvement. We propose the first fully automated AO retinal image montage procedure. Here, we present three novel fully automated registration methods, which are based on two established image processing approaches. The first method utilizes scale invariant feature transform (SIFT) in combination with specific image preprocessing. The second method uses the phase correlation (PC) approach and the last method is a connection of PC and SIFT (PC-SIFT) algorithm. In total, 200 images acquired from the left and right eyes of 10 subjects were used for creating the wide field-of-view montage images and compared with manual montaging. The automated image montage was successfully achieved. Alignment accuracy evaluated by normalized mutual information metric showed that the PC-SIFT approach established the most accurate results, these are higher than manual montaging. Therefore, the AO montaging registration methods are able to achieve promising results in accuracy and time demand in comparison with manual montaging. Hence, the latter can be replaced by those fully automated procedures.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20601 - Medical engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název statě ve sborníku

Annual Conference on Medical Image Understanding and Analysis

ISBN

978-3-030-80432-9

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

10

Strana od-do

503-513

Název nakladatele

Springer, Cham.

Místo vydání

Oxford, Great Britain

Místo konání akce

Oxford

Datum konání akce

12. 7. 2021

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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