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master's thesis
Robusna segmentacija slojeva retine dubokim učenjem
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. urn:nbn:hr:168:487111
Budimir, Lovre Antonio
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Budimir, L. A. (2020). Robusna segmentacija slojeva retine dubokim učenjem (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:487111

Budimir, Lovre Antonio. "Robusna segmentacija slojeva retine dubokim učenjem." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:487111

Budimir, Lovre Antonio. "Robusna segmentacija slojeva retine dubokim učenjem." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:487111

Budimir, L. A. (2020). 'Robusna segmentacija slojeva retine dubokim učenjem', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:487111

Budimir LA. Robusna segmentacija slojeva retine dubokim učenjem [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 November 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:487111

L. A. Budimir, "Robusna segmentacija slojeva retine dubokim učenjem", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:487111

Metadata
TitleRobusna segmentacija slojeva retine dubokim učenjem
Title (english)Robust Retinal Layer Segmentation Using Deep Learning
AuthorLovre Antonio Budimir
MentorSven Lončarić (mentor)
Committee memberSven Lončarić (predsjednik povjerenstva)
Committee memberMarko Subašić (član povjerenstva)
Committee memberTomislav Petković (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-07-14, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Segmentacija anatomskih struktura očne pozadine olakšava dijagnostiku i liječenje očnih bolesti. U diplomskog radu opisana je potpuno konvolucijska neuronska mreža za semantičku segmentaciju slojeva retine koja je temeljena na U-Net i EfficientNet arhitekturi. Eksperimenti provedeni u radu pokazali su kako odabrana arhitektura uspijeva postići bolje rezultate u usporedbi s najsuvremenijim metodama iz područja. Također, arhitektura je pokazala robusnost prilikom treniranja na slikama iz dva različita OCT uređaja. Dobri rezultati robusnih modela sugeriraju kako mreža uspijeva naučiti značajke koje razlikuju slojeve retine, te se ne oslanja na razlike u tehnikama snimanja između različitih OCT uređaja.
Abstract (english)
Segmentation of the anatomical structures of the ocular background facilitates the diagnosis and treatment of ocular diseases. This master's thesis has described a fully convolutional neural network for semantic segmentation of retinal layers based on U-Net and EfficientNet architecture. Experiments conducted in this thesis have shown that the selected architecture achieves better results compared with the state-of-the-art methods in the field. Also, the architecture has shown robustness when training on images from two different OCT devices. Good results from robust models suggest that the network manages to learn features that distinguish retinal layers and does not rely on differences in imaging techniques between different OCT devices.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:487111
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2023-01-13 11:55:08