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Automatic pupil detection using off-axis iris images for alignment guidance in fundus cameras

Dave, Poojan; Wei, Andrew; Nolan, David; Stock, Simon; Guo, Jing; Covita, Angelina; Chen, Michael; Straub, Jochen; Durbin, Mary; Manivannan, Niranchana

Abstract (englisch):
Purpose : The purpose of this study is to create a pupil tracking algorithm to find the center of the pupil within 400 micrometers of ground truth (manual annotations) in non-mydriatic external eye images. Pupil detection is crucial for automation and alignment guidance, which can improve the quality of fundus image acquisitions.

Methods : In the ultra-widefield fundus imaging system CLARUSTM 500 (ZEISS, Dublin, CA), two iris cameras provide an off-axis view of the patient’s eye along with the position of the pupil within the field of view. In this retrospective study, we used 654 external eye images (pixel size: 320x240) of non-mydriatic pupils (<3.5 mm pupil size) from 29 subjects. Manual annotations of pupil boundary and the center were marked by an expert grader. The dataset is divided into training (534 images from 18 subjects) and testing sets (120 images from 11 subjects).
Fig 1 shows the flowchart of the proposed pupil detection algorithm. The algorithm consists of two blocks: 1) coarse region-of-interest (ROI) finder and 2) fine-tuned pupil detector. Coarse ROI finder consisted of a single-shot detector (SSD) with 7 convolutional neural networks (CNN). ... mehr



Zugehörige Institution(en) am KIT Institut für Technik der Informationsverarbeitung (ITIV)
Publikationstyp Zeitschriftenaufsatz
Jahr 2019
Sprache Englisch
Identifikator ISSN: 0146-0404, 1552-5783
KITopen-ID: 1000104733
Erschienen in Investigative ophthalmology & visual science
Band 60
Heft 11
Seiten PB040
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