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scientific master's theses
Računalom potpomognuto učenje u internoj medicini zasnovano na digitalnoj obradi slike
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2008. urn:nbn:hr:168:047426
Šamšalović, Marko
University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Electronics, Microelectronics, Computer and Intelligent Systems

Cite this document

Šamšalović, M. (2008). Računalom potpomognuto učenje u internoj medicini zasnovano na digitalnoj obradi slike (Scientific master's theses). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:047426

Šamšalović, Marko. "Računalom potpomognuto učenje u internoj medicini zasnovano na digitalnoj obradi slike." Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, 2008. https://urn.nsk.hr/urn:nbn:hr:168:047426

Šamšalović, Marko. "Računalom potpomognuto učenje u internoj medicini zasnovano na digitalnoj obradi slike." Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, 2008. https://urn.nsk.hr/urn:nbn:hr:168:047426

Šamšalović, M. (2008). 'Računalom potpomognuto učenje u internoj medicini zasnovano na digitalnoj obradi slike', Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 20 April 2024, https://urn.nsk.hr/urn:nbn:hr:168:047426

Šamšalović M. Računalom potpomognuto učenje u internoj medicini zasnovano na digitalnoj obradi slike [Scientific master's theses]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2008 [cited 2024 April 20] Available at: https://urn.nsk.hr/urn:nbn:hr:168:047426

M. Šamšalović, "Računalom potpomognuto učenje u internoj medicini zasnovano na digitalnoj obradi slike", Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2008. Available at: https://urn.nsk.hr/urn:nbn:hr:168:047426

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Metadata
TitleRačunalom potpomognuto učenje u internoj medicini zasnovano na digitalnoj obradi slike
Title (english)Computer aided learning in internal medicine based on digital image processing
AuthorMarko Šamšalović
VIAF: 305655240
MentorZoran Kalafatić (mentor)
Committee memberSven Lončarić (predsjednik povjerenstva)
Committee memberZoran Kalafatić (član povjerenstva)
Committee memberŽeljko Hocenski (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
(Department of Electronics, Microelectronics, Computer and Intelligent Systems)
Zagreb
Defense date and country2008-11-27, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Data Processing
Universal decimal classification
(UDC)		004 - Computer science and technology. Computing. Data processing
61 - Medical sciences
Abstract
Jedan od većih problema kod ultrazvučne dijagnostike je u tome što dijagnostičar mora imati dosta iskustva za tumačenje ultrazvučnih slika. Ovaj magistarski rad bavi se načinima kako pomoći mladim liječnicima i studentima medicine u bržem svladavanju tog problema. Predloženi algoritmi za pomoć pri učenju pronalaženja granica u ultrazvucima su morfološki gradijent (s dva različita strukturna elementa), Sobelov operator i Cannyjev algoritam. Za svaki od algoritama je razvijena i priprema slike radi dobivanja što boljih rezultata. Parametri za algoritme i odgovarajuće pripreme slika određeni su na grupi ultrazvučnih slika štitnjače. Nakon toga su testirani na velikoj testnoj skupini ultrazvučnih slika i određen je najbolji algoritam. Na kraju su svi algoritmi ugrađeni u program za podršku učenju u internoj medicini i određene su buduće faze u razvoju dotičnog programa.
Abstract (english)
One of the biggest problems in ultrasound diagnostics is the fact that the person who is doing the diagnostics must have big experience to be able to interpret it correctly. These theses are about ways to aid young doctors and medicine students in faster acquiring of that experience. Following algorithms are proposed: morphological gradient (with two different structuring elements), Sobel operator and Canny algorithm. Image preparation for better results is developed for each of those algorithms. Parameters for those algorithms and image preparations are calculated on a group of thyroid gland ultrasounds. Algorithms were later tested on a large test group of ultrasounds and the best algorithm was found. All of the algorithms were later implemented in software for aid in learning in internal medicine. Next phases of software development were established.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:047426
Study programmeTitle: Postgraduate master programe in computing
Study programme type: university
Study level: postgraduate
Academic / professional title: magistar inženjer računarstva (magistar inženjer računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
RepositoryFER Repository
Created on2020-06-05 06:34:33

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