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Implementation of a tumor growth prediction system in reconfigurable logic

Malavazos Konstantinos

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URIhttp://purl.tuc.gr/dl/dias/02E4CAF2-A8AD-4804-A044-0627A7B0ED17-
Identifierhttps://doi.org/10.26233/heallink.tuc.77771-
Languageen-
Extent110 pagesen
TitleImplementation of a tumor growth prediction system in reconfigurable logicen
TitleΥλοποίηση σε αναδιατασσόμενη λογική συστήματος πρόγνωσης εξέλιξης όγκουel
CreatorMalavazos Konstantinosen
CreatorΜαλαβαζος Κωνσταντινοςel
Contributor [Thesis Supervisor]Papaefstathiou Ioannisen
Contributor [Thesis Supervisor]Παπαευσταθιου Ιωαννηςel
Contributor [Committee Member]Dollas Apostolosen
Contributor [Committee Member]Δολλας Αποστολοςel
Contributor [Committee Member]Zervakis Michailen
Contributor [Committee Member]Ζερβακης Μιχαηλel
Contributor [Co-Supervisor]Papadogiorgaki Mariaen
Contributor [Co-Supervisor]Παπαδογιωργακη Μαριαel
Contributor [Co-Supervisor]Malakonakis Pavlosen
Contributor [Co-Supervisor]Μαλακωνακης Παυλοςel
PublisherΠολυτεχνείο Κρήτηςel
PublisherTechnical University of Creteen
Academic UnitΠολυτεχνείο Κρήτης::Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστώνel
DescriptionMaster Thesis submitted to the Department of Electrical and Computer Engineering of the Technical University of Crete for the degree of Master of Scienceen
Content SummaryIn the last few years, the biomedical community is increasingly taking advantage of the increasing computational power, both to manage and analyze data and to model biological processes. Biomedical software applications usually require significant computational power, especially when they include the processing and analysis of large amounts of data, such as medical image sequences. This Master Thesis targets the acceleration of three different mathematical models, which are developed in the Technical University of Crete to model and predict the spatio-temporal evolution of glioma, using Reconfigurable Logic. Glioma is a rapidly evolving type of brain cancer, well known for its aggressive and diffusive behavior. The modeling applications presented in this Thesis fall under the category of multi-compartmental continuum approaches and aim to simulate the spatio-temporal evolution of a glioma tumor in an isotropic and heterogeneous brain tissue, which consists of different anatomic structures. The first model is the Oxygen-Glucose Diffusion-Proliferation 2D Model, simulating the proliferative cells and the necrotic core as a result of hypoxic and hypoglycemic-cells death, in single MRI images. The second is the Simple Diffusion-Proliferation 3D Model, which simulates only the proliferative cells in a sequence of MRI slices. The last is the Oxygen-Glucose Diffusion-Proliferation 3D Model, which simulates the same behaviors of the glioma as the 2D Model, in a sequence of MRI slices. The hardware acceleration is achieved using the Trenz platform, model TE0808 UltraSOM, which consists of a Xilinx Zynq UltraScale+ FPGA and an ARM Cortex A-53. The FPGA implementations of these Models are compared with the corresponding OpenMP software implementations on two different high-end Server systems, with up to 40 threads (Hyper-Threading). The results showed that the FPGA accelerators achieved runtime speedup and are up to 14 times more power efficient.en
Type of ItemΜεταπτυχιακή Διατριβήel
Type of ItemMaster Thesisen
Licensehttp://creativecommons.org/licenses/by-nc-sa/4.0/en
Date of Item2018-07-09-
Date of Publication2018-
SubjectHLSen
SubjectHigh-level synthesis (HLS)en
SubjectRuntime speedupen
SubjectEnergy efficiencyen
SubjectBiomedical applicationen
SubjectMRI imagesen
SubjectGliomaen
SubjectHardware accelerationen
SubjectTumor growth prediction modelen
SubjectReconfigurable logicen
SubjectBandwidthen
SubjectHigh Performance Computingen
SubjectHPCen
SubjectSystem on Chipen
SubjectSoCen
SubjectField-Programmable Gate Arrayen
SubjectFPGAen
Bibliographic CitationKonstantinos Malavazos, "Implementation of a tumor growth prediction system in reconfigurable logic", Master Thesis, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2018el
Bibliographic CitationΚωνσταντίνος Μαλαβάζος, "Υλοποίηση σε αναδιατασσόμενη λογική συστήματος πρόγνωσης εξέλιξης όγκου", Μεταπτυχιακή Διατριβή, Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2018el

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