|
|
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.
|
|
|
Facial image restoration
Bako, Matúš ; Herout, Adam (referee) ; Hradiš, Michal (advisor)
In this thesis, I tackle the problem of facial image super-resolution using convolutional neural networks with focus on preserving identity. I propose a method consisting of DPNet architecture and training algorithm based on state-of-the-art super-resolution solutions. The model of DPNet architecture is trained on Flickr-Faces-HQ dataset, where I achieve SSIM value 0.856 while expanding the image to four times the size. Residual channel attention network, which is one of the best and latest architectures, achieves SSIM value 0.858. While training models using adversarial loss, I encountered problems with artifacts. I experiment with various methods trying to remove appearing artefacts, which weren't successful so far. To compare quality assessment with human perception, I acquired image sequences sorted by percieved quality. Results show, that quality of proposed neural network trained using absolute loss approaches state-of-the-art methods.
|
|
|
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.
|
|
|
MR image processing
Mrákava, Petr ; Smékal, Zdeněk (referee) ; Gescheidtová, Eva (advisor)
The subject of this bachelor's thesis is to become familiar with the methods of processing image acquired by techniques of nuclear magnetic resonance. It describes the gradual steps in the digitizing of the signal to the image data. But in the process a disturbing component is almost always created in the image, in particular noise, which causes image devaluation. Therefore, further work is focused mainly on eliminating present disturbing components. For the noise elimination, the widely used wavelet transformation is applied, which is implemented by banks of digital filters. The experimental part of this work deals with design of MR filtering method, optimal filtering parameters setting, decomposition of images into magnetic field map, and subsequent comparison of results obtained.
|
|
|
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.
|
|
|
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.
|
|
|
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.
|
|
|
Reconstruction of Missing Parts of the Face Using Neural Network
Marek, Jan ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
Cílem této práce je vytvořit neuronovou síť která bude schopna rekonstruovat obličeje z fotografií na kterých je část obličeje překrytá maskou. Jsou prezentovány koncepty využívané při vývoji konvolučních neuronových sítí a generativních kompetitivních sítí. Dále jsou popsány koncepty používané v neuronových sítích specificky pro rekonstrukci fotografií obličejů. Je představen model generativní kompetitivní sítě využívající kombinaci hrazených konvolučních vrstev a víceškálových bloků schopný realisticky doplnit oblasti obličeje zakryté maskou.
|
|
|
Determination of Objects Similarity Based on Image Information
Rajnoha, Martin ; Kamencay,, Patrik (referee) ; Beneš, Radek (referee) ; Burget, Radim (advisor)
Monitoring of public areas and their automatic real-time processing became increasingly significant due to the changing security situation in the world. However, the problem is an analysis of low-quality records, where even the state-of-the-art methods fail in some cases. This work investigates an important area of image similarity – biometric identification based on face image. The work deals primarily with the face super-resolution from a sequence of low-resolution images and it compares this approach to the single-frame methods, that are still considered as the most accurate. A new dataset was created for this purpose, which is directly designed for the multi-frame face super-resolution methods from the low-resolution input sequence, and it is of comparable size with the leading world datasets. The results were evaluated by both a survey of human perception and defined objective metrics. A hypothesis that multi-frame methods achieve better results than single-frame methods was proved by a comparison of both methods. Architectures, source code and the dataset were released. That caused a creation of the basis for future research in this field.
|
|
|
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.
|
guest ::
