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master's thesis
Segmentacija panoramskih rendgenskih snimaka ljudske čeljusti
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:898260
Dorić, Gabriela
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Dorić, G. (2021). Segmentacija panoramskih rendgenskih snimaka ljudske čeljusti (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:898260

Dorić, Gabriela. "Segmentacija panoramskih rendgenskih snimaka ljudske čeljusti." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:898260

Dorić, Gabriela. "Segmentacija panoramskih rendgenskih snimaka ljudske čeljusti." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:898260

Dorić, G. (2021). 'Segmentacija panoramskih rendgenskih snimaka ljudske čeljusti', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 26 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:898260

Dorić G. Segmentacija panoramskih rendgenskih snimaka ljudske čeljusti [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 December 26] Available at: https://urn.nsk.hr/urn:nbn:hr:168:898260

G. Dorić, "Segmentacija panoramskih rendgenskih snimaka ljudske čeljusti", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:898260

Metadata
TitleSegmentacija panoramskih rendgenskih snimaka ljudske čeljusti
Title (english)Segmentation of Panoramic X-ray Images of Human Jaw
AuthorGabriela Dorić
MentorMarko Subašić (mentor)
Committee memberMarko Subašić (predsjednik povjerenstva)
Committee memberSven Lončarić (član povjerenstva)
Committee memberKrešimir Križanović (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-07-12, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Segmentacija slike zadatak je iz područja računalnog vida i svoju primjenu pronalazi u mnogim industrijama poput medicine i industrije autonomnih vozila. U okviru ovog rada istražena je primjena navedene metode u analizi dentalnih slika, odnosno primjena segmentacije na panoramskim rendgenskim snimkama ljudske čeljusti. Objašnjeni su temeljni koncepti dubokog učenja te su opisani korišteni algoritmi detekcije i segmentacija objekata. Za treniranje mreže korištena je state-of-the-art arhitektura Mask RCNN koja paralelno detektira i segmentira objekte na slici. Kao radna okolina za treniranje modela korišten je radni okvir Tensorflow. Model je treniran na umjetno stvorenim snimkama te je evaluiran na stvarnim snimkama. Dobiveni rezultati potvrđuju da je segmentacija objekta koristan alat u dentalnoj industriji te da umjetno generirani podatci mogu nadomjestiti nedostatak označenih podataka te na taj način smanjiti potrošnju vremenskih i novčanih resursa.
Abstract (english)
Image segmentation is a task in the field of digital image processing and computer vision, and as such finds its application in many industries, for example medicine and the autonomous vehicle industry. Within this paper, the application of image segmentation was investigated in the analysis of dental images, i.e. the application of segmentation on panoramic X-rays of the human jaw. The basic concepts of deep learning and used algorithms for detection and segmentation of objects are described. The state-of-the-art Mask RCNN architecture was used to train the network, which detects and segments objects in the image in parallel. The Tensorflow framework was used as the working environment for model training. The model was trained on artificially created images and evaluated on actual images. The obtained results confirm that the image segmentation is a useful tool in the dental industry and that artificially generated data can compensate for the lack of labeled
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:898260
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 12:07:43