Tortuosity classification of corneal nerves images using a multiple-scale-multiple-window approach

Roberto Annunziata (Lead / Corresponding author), Ahmad Kheirkhah, Shruti Aggarwal, Bernardo M. Cavalcanti, Pedram Hamrah, Emanuele Trucco

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Classify in vivo confocal microscopy corneal images by tortuosity is complicated by the presence of variable numbers of fibres of different tortuosity level. Instead of designing a function combining manually selected features into a single coefficient, as done in the literature, we propose a supervised approach which selects automatically the most relevant combination of shape features from a pre-defined dictionary. To our best knowledge, we are the first to consider features at different spatial scales and show experimentally their relevance in tortuosity modelling. Our results, obtained with a set of 100 images and 20 fold cross-validation, suggest that multinomial logistic ordinal regression, trained on consensus ground truth from 3 experts, yields an accuracy indistinguishable, overall, from that of experts when compared against each other.
Original languageEnglish
Title of host publicationProceedings of the Ophthalmic Medical Image Analysis First International Workshop, OMIA 2014, Held in Conjunction with MICCAI 2014
EditorsXinjian Chen, Mona K. Garvin, Jimmy J. Liu
PublisherIowa Research Online
Pages113-120
Number of pages8
Publication statusPublished - 2014
EventOphthalmic Medical Image Analysis First International Workshop - Boston, United States
Duration: 14 Sep 201414 Sep 2014

Conference

ConferenceOphthalmic Medical Image Analysis First International Workshop
Abbreviated titleOMIA 2014
CountryUnited States
CityBoston
Period14/09/1414/09/14

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Annunziata, R., Kheirkhah, A., Aggarwal, S., Cavalcanti, B. M., Hamrah, P., & Trucco, E. (2014). Tortuosity classification of corneal nerves images using a multiple-scale-multiple-window approach. In X. Chen, M. K. Garvin, & J. J. Liu (Eds.), Proceedings of the Ophthalmic Medical Image Analysis First International Workshop, OMIA 2014, Held in Conjunction with MICCAI 2014 (pp. 113-120). Iowa Research Online.