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Acceleration of Photoacoustic Imaging
 Nedeljković, Sava ; Bordovský, Gabriel (oponent) ; Jaroš, Jiří (vedoucí práce)
The goal of this thesis is to provide a new method of image reconstruction out of data generated using Photo-Acoustic imaging. Photo-Acoustic imaging is a very popular biomedical in-vivo imaging modality based on the non-invasive laser-induced generation of ultrasound waves recorded by the acoustic sensors, during which very large amounts of data are generated. The amount of data makes the image reconstruction process very time-consuming. This thesis demonstrates image reconstruction using Back-Projection, an algorithm that is simple enough to be optimized for execution on modern accelerated processor architectures. Two versions of this algorithm are designed: from the perspective of the pixel and from the perspective of the sensor. Both versions are implemented using 3 different execution acceleration methods: vector-level parallelism, thread-level parallelism, and parallelism on the Graphical Processing Unit (GPU). All 3 implementations of both algorithm versions are tested and their results are compared to the much slower but more accurate Time-Reversal reconstruction method. The results have shown that the GPU parallelism implementation offers the fastest execution, which is faster more than 200 times on average compared to the Time-Reversal method. This possibly makes it suitable even for real-time applications.
Úplný záznam
Acceleration of Photoacoustic Imaging
 Nedeljković, Sava ; Bordovský, Gabriel (oponent) ; Jaroš, Jiří (vedoucí práce)
The goal of this thesis is to provide a new method of image reconstruction out of data generated using Photo-Acoustic imaging. Photo-Acoustic imaging is a very popular biomedical in-vivo imaging modality based on the non-invasive laser-induced generation of ultrasound waves recorded by the acoustic sensors, during which very large amounts of data are generated. The amount of data makes the image reconstruction process very time-consuming. This thesis demonstrates image reconstruction using Back-Projection, an algorithm that is simple enough to be optimized for execution on modern accelerated processor architectures. Two versions of this algorithm are designed: from the perspective of the pixel and from the perspective of the sensor. Both versions are implemented using 3 different execution acceleration methods: vector-level parallelism, thread-level parallelism, and parallelism on the Graphical Processing Unit (GPU). All 3 implementations of both algorithm versions are tested and their results are compared to the much slower but more accurate Time-Reversal reconstruction method. The results have shown that the GPU parallelism implementation offers the fastest execution, which is faster more than 200 times on average compared to the Time-Reversal method. This possibly makes it suitable even for real-time applications.
Úplný záznam

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