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Projection and projection-reconstruction x-ray imaging process simulation
Fiala, Petr ; Jiřík, Radovan (referee) ; Drastich, Aleš (advisor)
The work deals with physical principles of X-ray generation and development of image during projection and projection reconstruction. A proposal of user’s application in a Matlab – Guide is given, which can be used as a laboratory exercise of the simulation of the projection- and projection image reconstruction. The computer program involves an evaluation of a X-ray quality of CT RTG ZS – quantitative assessment of spatial resolution and as well as the acquisition contrast as a function on an object size. The main aim of the work was the comparison of the acquisition contrast at various acquisition projection and projection-reconstruction parameters. Also, the work is illustrated by some results achieved.
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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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Superresolution
Mezera, Lukáš ; Dvořák, Radim (referee) ; Orság, Filip (advisor)
Úkolem této diplomové práce je navrhnout vlastní metodu pro zvýšení rozlišení v obraze scény, pokud je k dispozici více snímků dané scény. V teoretické části diplomové práce jsou jako nejlepší metody pro zvýšení rozlišení v obraze vybrány ty, které jsou založeny na principech zpracování signálu. Dále jsou popsány základní požadavky metod pro zvýšení rozlišení v obraze při přítomnosti více snímků stejné scény a jejich typická struktura. Následuje stručný přehled těchto metod a jejich vzájemné porovnání podle optimálních kritérií. Praktická část diplomové práce se zabývá samotným návrhem metody pro zvýšení rozlišení v obraze, pokud je k dispozici více snímků této scény. První navržená metoda je naimplementována a otestována. Při testování této metody je však zjištěna její špatná funkčnost pro snímky scény s nízkým rozlišením, které vznikly vzájemnou rotací. Z toho důvodu je navržena vylepšená metoda pro zvýšení rozlišení v obraze. Tato metoda využívá při svém výpočtu robustních technik. Díky tomu je již vylepšená metoda nezávislá na rotaci mezi snímky scény s nízkým rozlišením. I tato metoda je řádně otestována a její výsledky jsou porovnány s výsledky první navržené metody pro zvýšení rozlišení v obraze. V porovnání výpočetních časů je lepší první navrhovaná metoda, avšak její výsledky pro obrazy obsahující rotace nejsou kvalitní. Oproti tomu pro obrazy, které vznikly pouze posunem při snímání scény, jsou tyto výsledky velice dobré. Vylepšená metoda je tedy využitelná zejména pro obrazy obsahující rotace. V závěru této práce je ještě navrženo jedno vylepšení, které by mohlo zlepšit výsledky druhé navrhnuté metody pro zvýšení rozlišení v obraze scény.
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Neural Network Based Image Modifications
Maslowski, Petr ; Zbořil, František (referee) ; Šůstek, Martin (advisor)
This thesis deals with image colorization and image super-resolution using neural networks. It briefly explains neural networks principles and summarizes current approaches in this domain. It also describes the design, implementation and training of various neural network architectures. The best implemented architecture can colorize images, in particular, works well with outdoor areas. The architecture for image super-resolution with residual blocks that was trained with a perceptual loss function performs a double increase in image resolution (4x more pixels in total). Part of this thesis is also an implementation of a web application that uses trained models for image modification.
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X-ray computed tomography fluoroscopy simulation
Bainar, Petr ; Kolář, Radim (referee) ; Drastich, Aleš (advisor)
The aim of this thesis is to create simulator of image reconstruction during x-ray computed tomography fluoroscopy. Simulator will be put to use in laboratory exercises concerning imaging systems. Introductory part is focused on description of x-ray CT imaging process. Emphasis is placed especially on specific fluoroscopic reconstruction algorithms. In following part of thesis, the concept of simulator is analyzed-its inputs and outputs are declared and user’s operation is sketched out. Consequently, appearance and controls of realized simulator are described in detail. In evaluative part of thesis, achieved findings are documented. Influence of process parameters on acquired images is described, in this part. Consequently, optimal preferences finding method is suggested. Manual for laboratory exercise is attached.
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Interactive 3D CT Data Segmentation Based on Deep Learning
Trávníčková, Kateřina ; Hradiš, Michal (referee) ; Kodym, Oldřich (advisor)
This thesis deals with CT data segmentation using convolutional neural nets and describes the problem of training with limited training sets. User interaction is suggested as means of improving segmentation quality for the models trained on small training sets and the possibility of using transfer learning is also considered. All of the chosen methods help improve the segmentation quality in comparison with the baseline method, which is the use of automatic data specific segmentation model. The segmentation has improved by tens of percents in Dice score when trained with very small datasets. These methods can be used, for example, to simplify the creation of a new segmentation dataset.
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Reconstruction of Sparse Sampled Images with Deep Learning
Le, Hoang Anh ; Hradiš, Michal (referee) ; Juránek, Roman (advisor)
The main goal of this thesis was to increase reconstruction quality of sparse sampled microscopic images by using neural networks. The thesis will cover various approaches for image reconstruction and will also include descriptions of implementations, which were used. Implementations will be evaluated based on quality of reconstruction, but also based on segmentation, which could be their main possible application.
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X-ray computed tomography fluoroscopy simulation
Bainar, Petr ; Kolář, Radim (referee) ; Drastich, Aleš (advisor)
The aim of the thesis is to design and implement a simulator of image reconstruction during x-ray computed tomography fluoroscopy. Apart from quantitative evaluation of particular imaging process parameters influence, the intended program application will lie in optimization of these parameter values. Introductory part is focused on brief theoretical description of x-ray computed tomography imaging process. Emphasis is placed on fluoroscopy-specific approaches, particularly the division of scanned projections into chosen amount of sectors as well as fluoroscopic imaging process evaluation methods. The subsequent part deals with program implementation and its limitations and sketches the possible working framework. Moreover, one of the chapters is devoted to optimization of imaging process parameters measurement. The final part aims at impact analysis of particular process parameters as well as fluoroscopic imaging process optimization approaches. The thesis consists also of a didactic simulator enabling real-time intervention simulation with manual instrument manipulation. Since both simulators are intended for teaching purposes, the thesis is supplemented with a laboratory exercise draft.
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Reconstruction of Facial Images Using Neural Networks
Zubalík, Petr ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
The main purpose of this bachelor's thesis is to propose and implement a model, using neural networks, that will be able to reconstruct low-resolution facial images with blurry parts of the face. The task of super-resolution of facial images is solved by two models based on convolutional neural networks. The first model is built upon the architecture of ResNet whereas the other model makes use of the principles of generative adversarial networks. The proposed models are implemented in the Python programming language with the use of application programming interface of the TensorFlow framework. Moreover, as a part of this work, an application with a simple grafical user interface was created. This application makes it easy to use the implemented models. Several experiments are analyzed in the last chapter of this thesis to evaluate the performance of the models.
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Control of an interference-microscope optical stage based on the image phase
Kvasnica, Lukáš ; Číp, Ondřej (referee) ; Chmelík, Radim (advisor)
Digital holographic microscopy is an interferometric imaging technique, the principle of which is the off-axis image plane holography. The principle of this technique enables to reconstruct both the image intensity and the image phase from the output interferencesignal. The reconstruction can be carried out on the basis of a single image plane hologram. This leads to the possibility of a realtime image reconstruction. The speed of the reconstruction depends on the detection and the computing process. The aim of this diploma thesis is to develop user software for the control of the detection camera and for the image plane hologram reconstruction. The effort was to achieve the highest number of image reconstructions per time unit, with the maximum utilization of the data transfer between the camera and the computer.The next aim of this thesis is the stabilization of the optical table position. The method of stabilization is based on the image phase information, which is used for the control loop feedback between reconstructed image phase and the piezoelectric actuator placed inside of the optical table. Experimental results, which prove the functionality of the stabilization, are presented.
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