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master's thesis
Akcelerirana rekonstrukcija slika magnetske rezonancije temeljena na dubokim difuzijskim modelima.
Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2024. urn:nbn:hr:200:679910
Krčmar, Tea
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Software Engineering
Chair of Visual Computing

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Krčmar, T. (2024). Akcelerirana rekonstrukcija slika magnetske rezonancije temeljena na dubokim difuzijskim modelima. (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:679910

Krčmar, Tea. "Akcelerirana rekonstrukcija slika magnetske rezonancije temeljena na dubokim difuzijskim modelima.." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2024. https://urn.nsk.hr/urn:nbn:hr:200:679910

Krčmar, Tea. "Akcelerirana rekonstrukcija slika magnetske rezonancije temeljena na dubokim difuzijskim modelima.." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2024. https://urn.nsk.hr/urn:nbn:hr:200:679910

Krčmar, T. (2024). 'Akcelerirana rekonstrukcija slika magnetske rezonancije temeljena na dubokim difuzijskim modelima.', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 18 March 2025, https://urn.nsk.hr/urn:nbn:hr:200:679910

Krčmar T. Akcelerirana rekonstrukcija slika magnetske rezonancije temeljena na dubokim difuzijskim modelima. [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2024 [cited 2025 March 18] Available at: https://urn.nsk.hr/urn:nbn:hr:200:679910

T. Krčmar, "Akcelerirana rekonstrukcija slika magnetske rezonancije temeljena na dubokim difuzijskim modelima.", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:200:679910

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Metadata
TitleAkcelerirana rekonstrukcija slika magnetske rezonancije temeljena na dubokim difuzijskim modelima.
Title (english)Accelerated Reconstruction of Magnetic Resonance Images Based on Deep Diffusion Models
AuthorTea Krčmar
MentorIrena Galić (mentor)
MentorMarija Habijan (sumentor)
Committee memberMarija Habijan (predsjednik povjerenstva)
Committee memberKrešimir Nenadić (član povjerenstva)
Committee memberKrešimir Romić (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Software Engineering)
(Chair of Visual Computing)
Osijek
Defense date and country2024-10-22, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Artificial Intelligence
Abstract
Ovaj diplomski rad istražuje primjenu dubokih difuzijskih modela za akceleriranu rekonstrukciju slika magnetske rezonancije mozga. Rad pruža pregled područja magnetske rezonancije, uključujući tehnike akvizicije i suvremene metode rekonstrukcije. Predstavljen je novi model temeljen na difuzijskim modelima s inovativnim pristupom dinamičkog uzorkovanja $k$-prostora. Evaluacija modela na dva različita skupa podataka pokazuje poboljšanja u brzini i preciznosti rekonstrukcije u odnosu na ... More tradicionalne i suvremene metode. Kvantitativna i kvalitativna analiza rezultata potvrđuje uspješnost modela uz prostor za buduću nadogradnju i optimizaciju posebno u radu s podacima u k-prostoru. Less
Abstract (english)
This thesis investigates the application of deep diffusion models for accelerated reconstruction of brain magnetic resonance imaging. The thesis provides an overview of the field of magnetic resonance imaging, including acquisition techniques and state-of-the-art reconstruction methods. A novel diffusion-based model is introduced, featuring an innovative dynamic $k$-space sampling approach. Evaluation of the model on two different datasets demonstrates improvements in both ... More reconstruction speed and accuracy compared to traditional and contemporary methods. Quantitative and qualitative analysis of the results confirms the effectiveness of the model while also highlighting the potential for future enhancements and optimization, particularly in handling k-space data. Less
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:679910
Study programmeTitle: Graduate University Study Programme in Computer Engineering
Study programme type: university
Study level: graduate
Academic / professional title: sveučilišni/a magistar/magistra inženjer/inženjerka računarstva (sveučilišni/a magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
RepositoryFaculty of Electrical Engineering, Computer Science and Information Technology Osijek
Created on2024-10-23 07:18:49
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