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Fast Tissue Image Reconstruction Using a Graphics Card
Kadlubiak, Kristián ; Kula, Michal (referee) ; Jaroš, Jiří (advisor)
The photoacoustic spectroscopy is a recently developed imaging method that finds applications in many scientific fields such as medicine, biochemistry, materials engineering and many others. The photoacoustic spectroscopy finds particularly nice applications in medicine due to its properties such as non-invasiveness, non-aggressiveness and great accuracy. The source of this accuracy lies in advanced time-consuming calculations including operations like FFT and trilinear interpolation. This thesis is dedicated to the acceleration of this technique on a graphics card. In our implementation, we have taken a full advantage of various features provided in modern GPUs such as shared memory and texture hardware. Our implementation has been tested on one of the most powerful GPU designed for high performance computing, namely NVIDIA K20m. In this environment, our application speeds up certain parts of reconstruction by a factor above 400. In a single run mode, the whole reconstruction runs a bit longer than the pure MATLAB version due to the necessity of transferring data between MATLAB and the CUDA code, although the developed approach reduced the data transfers between MATLAB and GPU by 37%. The real potential of the implementation reveals while processing large batches of photoacoustic images.
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Micro-mechanical Sensor and Laser Photoacoustics for Diagnostics in Gases
Vlasáková, Tereza ; Nesměrák, Karel (advisor) ; Wild, Jan (referee)
The aim of the thesis is to study mechanical properties of nanomaterials (multi-layer graphene, silicon, mica) suitable to be used as novel pressure sensors in laser photoacoustic spectroscopy. Membranes (diameter ~ 4 mm, thickness ~ 100 nm) were prepared by mechanical exfoliation method and then attached to a glass window in several slightly different designs. Movement of these membranes was detected using HeNe laser beam reflected from the membrane's surface onto a position sensitive detector. Methanol was used as a model gas and the signal was collected from studied element and microphone simultaneously. Acoustic wave, induced inside a measuring cell by periodic thermal variations, causes the membranes to move. The movement of a membrane is influenced by its mechanical properties, which is possible to determine by fitting the measured data into a mathematical model. Comparison of the output data of all membranes' measurements shows, that the signal intensity is influenced by the method of attaching membrane to a glass window and by volume of free space on a side of a membrane. Metallization of the membrane's surface (~ 70 nm) decreases its springiness thus decreases the sensitivity. Several membranes reached sensitivity comparable with top class microphone.
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Fast Tissue Image Reconstruction Using a Graphics Card
Kadlubiak, Kristián ; Kula, Michal (referee) ; Jaroš, Jiří (advisor)
The photoacoustic spectroscopy is a recently developed imaging method that finds applications in many scientific fields such as medicine, biochemistry, materials engineering and many others. The photoacoustic spectroscopy finds particularly nice applications in medicine due to its properties such as non-invasiveness, non-aggressiveness and great accuracy. The source of this accuracy lies in advanced time-consuming calculations including operations like FFT and trilinear interpolation. This thesis is dedicated to the acceleration of this technique on a graphics card. In our implementation, we have taken a full advantage of various features provided in modern GPUs such as shared memory and texture hardware. Our implementation has been tested on one of the most powerful GPU designed for high performance computing, namely NVIDIA K20m. In this environment, our application speeds up certain parts of reconstruction by a factor above 400. In a single run mode, the whole reconstruction runs a bit longer than the pure MATLAB version due to the necessity of transferring data between MATLAB and the CUDA code, although the developed approach reduced the data transfers between MATLAB and GPU by 37%. The real potential of the implementation reveals while processing large batches of photoacoustic images.
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