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Ubrzanje algoritama za segmentaciju biomedicinskih slika korišćenjem rekonfigurabilne hardverske platforme

Acceleration of algorithms for biomedical images segmentation using reconfigurable hardware platform

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2019
Disertacija.pdf (6.297Mb)
Ivan_Milankovic_FIN.pdf (2.404Mb)
Author
Milanković, Ivan
Mentor
Peulić, Aleksandar
Committee members
Filipović, Nenad
Jorgovanović, Nikola
Milovanović, Vladimir
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Abstract
REZIME: Obrada slike predstavlja jednu od najčešće primenjivanih metoda u biomedicinskoj dijagnostici, a segmentacija biomedicinskih slika predstavlja jedan od prvih koraka prilikom obrade biomedicinskih slika. Segmentacijom se slike grupišu u segmente koji poseduju odgovarajuće zajedničke karakteristike i time čine sliku jasnijom i lakšom za dalju obradu. Razvojem sistema za akviziciju biomedicinskih slika dobijaju se slike boljeg kvaliteta i veće rezolucije. Takođe, u sistemima gde se vrše snimanja pacijenata u cilju trodimenzionalne rekonstrukcije određenih organa, smanjuje se razmak između dva susedna snimka, odnosno dva susedna preseka. Time se postiže znatno bolja prostorna rezolucija, ali i znatno veći broj slika koje treba obraditi. Upravo zbog ovog stalnog napretka sistema za akviziciju slika, aplikacije za obradu istih postaju sve zahtevnije za procesiranje. Imajući u vidu sve gore navedeno, jasno je da je jedan od glavnih zadataka istraživača ubrzanje algoritam...a za obradu slika. Ubrzanje se može postići ili poboljšanjem koda algoritma ili prebacivanjem izvršenja algoritma na druge platforme. Pregledom literature došlo se do zaključka da rekonfigurabilna hardverska platforma daje odlične rezultate u obradi slika. U okviru ove doktorske disertacije predložena su tri algoritma za segmentaciju biomedicinskih slika. To su algoritam za segmentaciju mamografskih slika grudi, algoritam za segmentaciju mikrotomografskih slika poprečnih preseka mišjih pluća iii algoritam za segmentaciju slika poprečnih preseka kolena dobijenih metodom računarske tomografije. Sva ova tri algoritma su detaljno objašnjena i prikazani su njihovi rezultati obrade slika. Zadatak ove doktorske disertacije je prebacivanje ovih algoritama na rekonfigurabilnu hardversku platformu u cilju poboljšanja njihovih performansi. Sva tri algoritma su uspešno prebačena na rekonfigurabilnu hardversku platformu, pri čemu je dat detaljan opis efikasnog prebacivanja algoritama, kao i toka podataka kroz graf rekonfigurabilne hardverske platforme. Eksperimentalni rezultati su pokazali da se rekonfigurabilna hardverska platforma može uspešno koristiti u cilju ubrzanja algoritama za segmentaciju biomedicinskih slika.

ABSTRACT: Image processing represents one of the most common procedures in biomedical diagnostic systems. Biomedical image segmentation represents one of the first steps in biomedical image processing. Image segmentation divides image into multiple segments with common characteristics which makes the image easier for further processing. With development of biomedical acquisition systems produced images are with much higher quality and resolution. Also, in systems where patients are recorded for 3D image reconstruction, space between two neighbor slices reduces constantly. Thus, we have much better 3D resolution, but also there is much more images which we need to process. Because of that, applications for image processing start to require much more processor time and resources. Based on all of this, it is clear that one of the main tasks of scientists and researchers is to accelerate image processing algorithms. That acceleration can be achieved by improving the algorithm i...tself or by porting algorithm to another platform. In literature, there can be found more and more researches in which reconfigurable hardware platform is used to accelerate some algorithms for image processing In this dissertation three algorithms for biomedical images segmentation are proposed. Those are algorithm for segmentation of breast mammogram images, algorithm for microtomograph murine lungs images segmentation and algorithm for CT knee images segmentation. All of these three algorithms are explained in details and the results of their processing are presented.iv The main task of this dissertation is porting of those algorithms to reconfigurable hardware platform in order to boost their performances. All three algorithms are successfully ported to reconfigure hardware platform and the detailed description of that porting is presented. Also, the detail description of data flow through graph of reconfigurable hardware platform is described. Experimental results showed that reconfigurable hardware platform can be successfully used for accelerating of biomedical image segmentation.

Faculty:
University of Kragujevac, Faculty of Engineering
Date:
16-09-2019
Projects:
  • Functional, Functionalized and Advanced Nanomaterials (RS-45005)
Keywords:
rekonfigurabilna hardverska platforma / reconfigurable hardware platform / segmentacija biomedicinskih slika / mamografske slike grudi / mikrotomografske slike mišjih pluća / slike kolena dobijene računarskom tomografijom. / biomedical image segmentation / breast mammogram images / micro-tomography murine lungs images / CT knee images.
[ Google Scholar ]
Handle
https://hdl.handle.net/21.15107/rcub_nardus_11988
URI
http://eteze.kg.ac.rs/application/showtheses?thesesId=7156
https://nardus.mpn.gov.rs/handle/123456789/11988
https://fedorakg.kg.ac.rs/fedora/get/o:1212/bdef:Content/download

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