4D medical data compression architecture

doctoral thesis

• Title (croatian): Arhitektura sustava za kompresiju četverodimenzionalnih medicinskih podataka
• Author: Martin Žagar
• Mentor: Mario Kovač (mentor)
• Committee member: Hrvoje Mlinarić (predsjednik povjerenstva)
• Committee member: Mario Kovač (član povjerenstva)
• Committee member: Davor Antonić (član povjerenstva)
• Committee member: Nagarajan Ranganathan (član povjerenstva); strani drzavljanin: Nije dostupno
• Committee member: Damir Bakić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; (Department of Control and Computer Engineering); Zagreb
• Defense date and country: 2009-02-02, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing
• Universal decimal classification (UDC): 004 - Computer science and technology. Computing. Data processing

Abstract

This thesis presents a novel framework for four-dimensional medical data compression architecture. This framework is based on different procedures and algorithms that detect time and spatial redundancy in recorded MRI volumes. Motion in time is analyzed through motion estimation based on neural networks. Motion estimation is used to eliminate a large amount of temporal and frequency redundancies that exists in sequences of 3D data. Combination of segmentation, block matching and motion field prediction along with expert knowledge are incorporated to achieve better performance. Frequency analysis is done through an extension of wavelet transformations to three dimensions. For still volume objects different wavelet packets with different filter banks can be constructed, providing a wide range of frequency analysis. With combination of removing temporal and spatial redundancies, very high compression ratio is achived. The suggested data compression architecture can be implemented in telemedicine to improve the quality of service. It incorporates operations for frequency and time analysis of datasets, creating kernel shapes and models, and fitting of medical 4D datasets. Each part of the system architecture is implemented independently and can be used for other approaches such as entertainment applications and other new applications that use 4D data.

Abstract (croatian)

U ovom doktorskom radu prezentirane su osnovne značajke arhitekture za četverodimenzionalnu kompresiju medicinskih podataka koja se temelji na različitim procedurama i algoritmima za analizu vremenske i prostorne zalihosti MR zapisa u NIfTI podatkovnom formatu. Za analizu i procjenu pokreta, a u cilju uklanjanja vremenske zalihosti koja postoji u slijedu 3D prostornih podataka koriste se neuronske mreže. Da bi se ostvarila kompresija takvih podataka, koristi se ekspertno znanje u različitim algoritmima segmentacije podataka, procjene oblika, predviđanja i definiranja polja pokreta. Frekvencijska analiza je ostvarena proširenjem transformacije temeljene na teoriji valića u tri dimenzije. Za statičke 3D prostorne podatke koriste se različite baze i paketi valića koji pružaju širok raspon frekvencijske analize. Uklanjanjem vremenske i prostorne zalihosti postiže se visok stupanj kompresije. Predložena arhitektura kompresije služi u podizanju razine kvalitete usluga u telemedicini. Svaki dio ove arhitekture predstavlja zasebnu cjelinu te se može primijeniti nezavisno i u druge svrhe, kao što su aplikacije namijenjene zabavi i druge aplikacije koje koriste četverodimenzionalne podatke.

• Keywords: 4D medical datasets; time and frequency redundancy; 3D wavelet transform; motion field; motion estimation based on neural networks; medical data segmentation; shape estimation; medical data compression
• Keywords (croatian): četverodimenzionalni medicinski skupovi podataka; vremenska i frekvencijska zalihost; trodimenzionalna transformacija temeljena na teoriji valića; polje pokreta; procjena pokreta temeljan na neuronskim mrežama; segmentacija medicinskih podataka; procjena oblika; kompresija medicinskih podataka
• Language: english
• URN:NBN: urn:nbn:hr:168:208725
• Study programme: Title: Computer Science; Study programme type: university; Study level: postgraduate; Academic / professional title: Doktor znanosti (Doktor znanosti)
• Catalog URL: http://lib.fer.hr/cgi-bin/koha/opac-detail.pl?biblionumber=33251
• Type of resource: Text
• Extent: 202 str.
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2020-03-19 11:25:11