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master's thesis
3D segmentacija CT snimaka bubrežnog kamenca
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2014. urn:nbn:hr:168:144249
Đonlić, Matea
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Đonlić, M. (2014). 3D segmentacija CT snimaka bubrežnog kamenca (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:144249

Đonlić, Matea. "3D segmentacija CT snimaka bubrežnog kamenca." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2014. https://urn.nsk.hr/urn:nbn:hr:168:144249

Đonlić, Matea. "3D segmentacija CT snimaka bubrežnog kamenca." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2014. https://urn.nsk.hr/urn:nbn:hr:168:144249

Đonlić, M. (2014). '3D segmentacija CT snimaka bubrežnog kamenca', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 16 June 2024, https://urn.nsk.hr/urn:nbn:hr:168:144249

Đonlić M. 3D segmentacija CT snimaka bubrežnog kamenca [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2014 [cited 2024 June 16] Available at: https://urn.nsk.hr/urn:nbn:hr:168:144249

M. Đonlić, "3D segmentacija CT snimaka bubrežnog kamenca", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2014. Available at: https://urn.nsk.hr/urn:nbn:hr:168:144249

Metadata
Title3D segmentacija CT snimaka bubrežnog kamenca
Title (english)3D segmentation of kidney stone CT images
AuthorMatea Đonlić
MentorDamir Seršić (mentor)
Committee memberDamir Seršić (predsjednik povjerenstva)
Committee memberMladen Vučić (član povjerenstva)
Committee memberMarko Subašić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2014-07-09, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Ovaj diplomski rad usmjeren je na implementaciju i usporedbu različitih metoda 3D segmentacije s primjenom na problem segmentacije CT snimaka bubrežnog kamenca. Budući da se sve metode 3D segmentacije provode nad diskretnom trodimenzionalnom rešetkom, ulazni podaci (skup datoteka u DICOM formatu) obrađeni su i oblikovani tako da je omogućen odabir područja interesa i iz njega stvaranje diskretne rešetke. U sklopu rada, implementirane su metode amplitudne segmentacije, segmentacije izrastanjem područja te segmentacije temeljene na lokalnoj faznoj koherenciji. Kao ocjena uspješnosti segmentacije korištena je mjera sličnosti između napravljenog modela i referentnog modela izvađenog kamenca. Mjera sličnosti dobivena je provođenjem postupka registracije modela korištenjem ICP algoritma. Također, napravljena je usporedba s rezultatima segmentacija provedenih korištenjem dostupnih programskih alata za 3D medicinsku segmentaciju. Napravljena je i usporedba brzine izvođenja implementiranih segmentacija te ocjena uspješnosti segmentacija u ovisnosti o subjektivnim odabirima područja interesa.
Abstract (english)
This thesis focuses on the implementation and comparison of different 3D segmentation methods along with their application to the medical problem of kidney stone CT image segmentation. Considering the fact that the all segmentation methods require a discrete three-dimensional grid, the input data in DICOM format had to be processed and shaped in the form suitable for the process of region of interest (ROI) selection and the creation of the three-dimensional grid. Three 3D segmentation methods were presented and implemented in this thesis -- an amplitude segmentation method, a region growing segmentation and a segmentation method based on the local phase coherence. For the evaluation of implemented segmentation methods, created models were compared with surgically removed kidney stone and also with the models created using few of the available software tools for 3D medical segmentation. Models were compared based on the similarity measure obtained via ICP algorithm. Also, an execution time analysis for different segmentation methods was made as well as the comparison of the segmentation performance depending on the subjective choices of ROI.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:144249
Study programmeTitle: Information and Communication Technology
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka informacijske i komunikacijske tehnologije (magistar/magistra inženjer/inženjerka informacijske i komunikacijske tehnologije)
Type of resourceText
File originBorn digital
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Created on2018-02-06 08:38:46