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undergraduate thesis
Klasifikacija nepravilnosti u slikama kože
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:671021
Andreis, Marko
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Andreis, M. (2021). Klasifikacija nepravilnosti u slikama kože (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:671021

Andreis, Marko. "Klasifikacija nepravilnosti u slikama kože." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:671021

Andreis, Marko. "Klasifikacija nepravilnosti u slikama kože." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:671021

Andreis, M. (2021). 'Klasifikacija nepravilnosti u slikama kože', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:671021

Andreis M. Klasifikacija nepravilnosti u slikama kože [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 November 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:671021

M. Andreis, "Klasifikacija nepravilnosti u slikama kože", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:671021

Metadata
TitleKlasifikacija nepravilnosti u slikama kože
Title (english)Classification of Irregularities in Skin Images
AuthorMarko Andreis
MentorTomislav Hrkać (mentor)
Committee memberTomislav Hrkać (predsjednik povjerenstva)
Committee memberIgor Stančin (član povjerenstva)
Committee memberJosip Renić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-07-06, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Posljednjih nekoliko desetljeća bilježi se trend porasta pojavnosti melanoma – zloćudnog tumora kože. S obzirom na rezultate projekcija koje se rade za nadolazeće jednogodišnje razdoblje čini se kako će se taj trend nastaviti. Najvažniji faktor o kojemu ovisi uspješno tretiranje ove bolesti jest njeno rano i pravovremeno otkrivanje. S ciljem povećanja uspješnosti ispravnih detekcija i sprječavanja razvoja bolesti razvijaju se modeli strojnog učenja čija je namjera automatizirati detekciju zloćudnih tumora i njihovu klasifikaciju na temelju obilježja poput oblika, boje i veličine. Kod aplikacija koje uključuju obradu slike, poput postupka klasifikacije, svoju primjenu nalaze konvolucijske neuronske mreže. Cilj ovog rada jest pospješiti rano otkrivanje zloćudnih promjena na koži uporabom automatske, računalom potpomognute dijagnostike, konkretno, primjenom funkcionalnosti neuronskih mreža u problemu klasifikacije slika koje sadrže zloćudne promjene s ciljem povećanja uspješnosti liječenja. Nadalje, prikazani su postojeći pristupi klasifikaciji kožnih nepravilnosti i analizirano ponašanje implementiranih sustava.
Abstract (english)
The last few decades have seen an increasing trend in the incidence of melanoma – a malignant skin tumor. Given the results of the projections being made for the upcoming one-year period, it seems that this trend will continue. The most important factor on which the successful treatment of this disease depends is its early and timely detection. In order to increase the success of correct detection and prevent further development of the disease, machine learning models whose intention is to automate the detection of malignant tumors and their classification based on characteristics such as shape, color and size are being developed. Convolutional neural networks are being applied in applications that involve image processing, such as the classification process. The main goal of this paper is to improve the early detection of malignant irregularities found on the skin using automatic, computer-assisted diagnostics, specifically, by applying the functionalities of neural networks in the problems of classifying images containing malignant changes in order to increase treatment success. Furthermore, the existing approaches to the classification of skin irregularities are presented and the performance of the implemented systems is analyzed.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:671021
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2023-01-14 19:59:13