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Wyszukujesz frazę "rezonans magnetyczny" wg kryterium: Temat


Wyświetlanie 1-4 z 4
Tytuł:
Application of image registration techniques in dynamic magnetic resonance imaging of breast
Autorzy:
Kuczyński, K.
Siczek, M.
Stęgierski, R.
Powiązania:
https://bibliotekanauki.pl/articles/333314.pdf
Data publikacji:
2011
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
rejestracja obrazu
Rezonans magnetyczny wraz z kontrastem
rak piersi
image registration
DCE-MRI
breast cancer
Opis:
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a relatively new, promising technique for breast cancer diagnostics. A few series of images of the same body region are rapidly acquired before, during and after injection of paramagnetic contrast agent. Propagation of the contrast agent causes modification of MR signal over time. Its analysis provides information on tissue properties, including tumour status, that is not available with the regular MRI. Unintentional patient's movements during the examination result with incorrect alignment of the consecutive image series. Their analysis is then difficult, inaccurate or even impossible. The purpose of this work is to design a registration scheme that could be applied to solve the problem in a routine manner, in standard hospital conditions. The proposed registration framework, composed of B-spline transformation, mean squares metric and LBFGSB optimizer, is able to produce satisfactory results within reasonable time.
Źródło:
Journal of Medical Informatics & Technologies; 2011, 17; 275-280
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Functional magnetic resonance imaging of a brain - example results of examination
Autorzy:
Cichocka, M.
Powiązania:
https://bibliotekanauki.pl/articles/333320.pdf
Data publikacji:
2011
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
funkcjonalny rezonans magnetyczny
mózg
cyfrowe przetwarzanie
analiza obrazu
fMRI
brain
digital processing
image analysis
BOLD
NordicICE
Opis:
The article describes a functional magnetic resonance imaging (fMRI) examination and the further data analysis. Inspiration to take an interest in fMRI diagnostics was its cognitive and clinical use which was observed by the author during the student practice at the Cracow University Hospital Department of Radiology (1.5 T SIGNA EXCITE 2 Echospeed MR System). The author of the paper participated in fMRI study of a patient diagnosed with right brain hemisphere tumour. In this case it was necessary to determine active regions responsible for limbs' movement. The obtained diagnostic data were the object of further analysis (digital processing). The images of an anatomical structure of patient's brain (in greyscale) with colourful active areas were obtained by analyzing images using specialized software NordicICE 2.3.1 and Functool 2.6.6. Looking at such images, it is possible for a doctor to determine the changes in the brain at the molecular level and to plan eventual neurosurgery.
Źródło:
Journal of Medical Informatics & Technologies; 2011, 17; 309-312
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Automatic segmentation of brain tumors using tensor analysis and multimodal MRI
Autorzy:
Jackowski, K.
Manhães-Savio, A.
Cyganek, B.
Powiązania:
https://bibliotekanauki.pl/articles/333913.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
brain lesion
MRI
magnetic resonance imaging
classification
tensor
zmiany w mózgu
rezonans magnetyczny
obrazowanie metodą rezonansu magnetycznego
klasyfikacja
Opis:
Glioma detection and classification is an critical step to diagnose and select the correct treatment for the brain tumours. There has been advances in glioma research and Magnetic Resonance Imaging (MRI) is the most accurate non-invasive medical tool to localize and analyse brain cancer.The scientific global community has been organizing challenges of open data analysis to push forward automatic algorithms to tackle this task. In this paper we analyse part of such challenge data, the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS), with novel algorithms using partial learning to test an active learning methodology and tensor-based image modelling methods to deal with the fusion of the multimodal MRI data into one space. A Random Forest classifier is used for pixel classification. Our results show an error rates of 0.011 up to 0.057 for intra-subject classification. These results are promising compared to other studies. We plan to extend this method to use more than 3 MRI modalities and present a full active learning approach.
Źródło:
Journal of Medical Informatics & Technologies; 2015, 24; 165-172
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analysis and comparison of symmetry based lossless and perceptually lossless algorithms for volumetric compression of medical images
Autorzy:
Chandrika, B. K.
Aparna, P.
Sumam, D. S.
Powiązania:
https://bibliotekanauki.pl/articles/333936.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
bilateral symmetry
human visual system
MRI image
CT image
just noticeable distortion
perceptually lossless compression
symetria dwustronna
obraz MRI
rezonans magnetyczny
obrazowanie metodą rezonansu magnetycznego
obraz CT
tomografia komputerowa
zniekształcenie
Opis:
Modern medical imaging techniques produce huge volume of data from stack of images generated in a single examination. To compress them several volumetric compression techniques have been proposed. Performance of these compression schemes can be improved further by considering the anatomical symmetry present in medical images and incorporating the characteristics of human visual system. In this paper a volumetric medical image compression algorithm is presented in which perceptual model is integrated with a symmetry based lossless scheme. Symmetry based lossless and perceptually lossless algorithms were evaluated on a set of three dimensional medical images. Experimental results show that symmetry based perceptually lossless coder gives an average of 8.47% improvement in bit per pixel without any perceivable degradation in visual quality against the lossless scheme.
Źródło:
Journal of Medical Informatics & Technologies; 2015, 24; 147-154
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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