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master's thesis
Segmentacija medicinskih slika primjenom dubokog učenja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:123728
Martinović, Filip
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Martinović, F. (2024). Segmentacija medicinskih slika primjenom dubokog učenja (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:123728

Martinović, Filip. "Segmentacija medicinskih slika primjenom dubokog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:123728

Martinović, Filip. "Segmentacija medicinskih slika primjenom dubokog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:123728

Martinović, F. (2024). 'Segmentacija medicinskih slika primjenom dubokog učenja', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 26 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:123728

Martinović F. Segmentacija medicinskih slika primjenom dubokog učenja [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2024 [cited 2024 December 26] Available at: https://urn.nsk.hr/urn:nbn:hr:168:123728

F. Martinović, "Segmentacija medicinskih slika primjenom dubokog učenja", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:123728

Metadata
TitleSegmentacija medicinskih slika primjenom dubokog učenja
Title (english)Segmentation of medical images using deep learning
AuthorFilip Martinović
MentorTomislav Hrkać (mentor)
Committee memberTomislav Hrkać (predsjednik povjerenstva)
Committee memberSiniša Šegvić (član povjerenstva)
Committee memberDomagoj Jakobović (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-09-20, Croatia
Abstract
U ovom radu raspravlja se o problemu segmentacije medicinskih slika na skupu podataka DRIVE. Skup sadrži slike mrežnice oka i segmentacijske maske koje sadrže žile. U radu se opisuju tradicionalne metode obrade slike i suvremene metode dubokog učenja. Na skupu podataka se uči segmentacijski model UNet sa ResNet34 koderom. Uspoređuju se rezultati na originalnom skupu, augmentiranom skupu i skupu na koji je primijenjena CLAHE transformacija.
Abstract (english)
In this paper, the problem of segmentation of medical images is discussed. The dataset used for experiments is DRIVE. The dataset contains retinal images and segmentation masks containing vessels. The paper describes traditional image processing methods and modern deep learning methods. The segmentation model UNet with the ResNet34 encoder is trained on the dataset. The results on the original dataset, the augmented dataset and the dataset with CLAHE transformation applied are compared.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:123728
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 on2024-10-12 21:29:10