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Wyszukujesz frazę "Śramek, M." wg kryterium: Autor


Wyświetlanie 1-4 z 4
Tytuł:
Region-based processing of volumetric data
Autorzy:
Hućko, M.
Śramek, M.
Powiązania:
https://bibliotekanauki.pl/articles/333404.pdf
Data publikacji:
2011
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
dane objętościowe i tomograficzne
przełom transformacji
region oparty na przetwarzaniu objętości
volumetric and tomographic data
watershed transform
region-based volume processing
Opis:
Measurement of volumetric tomographic data, similar to other measurement techniques, suffers from several classes of artifacts, of which noise presence and the partial volume effect belong to the most prominent ones. These artifacts spoil data analysis and/or visualization, which may, for example in the case of medical imaging, lead to erroneous decisions with severe consequences. We propose a set of tools for region-based processing of volumetric data. Here, the basic entity is a spectrally homogeneous region instead of the traditional voxel. This provides for, on the one hand, higher robustness and, on the other hand, speeds up processing owing to many times smaller amount of elements to work with. Homogeneous regions are in our approach detected by the well-known segmentation by means of the watershed transform. In this paper we present algorithms for streamed computation of watershed transform, which allows for processing of very large data, region-based data smoothing and region merging based on the spectral distance. Further, we present an interactive tool for volume data segmentation and visualization which takes advantage of region hierarchies obtained by a hierarchical watershed transform.
Źródło:
Journal of Medical Informatics & Technologies; 2011, 17; 247-253
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Segmentation of tomographic data by hierarchical watershed transform
Autorzy:
Sramek, M.
Dimitrov, L. I.
Powiązania:
https://bibliotekanauki.pl/articles/332935.pdf
Data publikacji:
2002
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
segmentacja obrazu
skala przestrzeni
image segmentation
hierarchical watershed transform
scale space
Opis:
The aim of the proposed watershed based image segmentation technique is to split images into spatially homogeneous regions, which can be further processed by different image analysis tools. The advantage of such approach, in comparison to pixel oriented processing, is its lower sensitivity to superimposed noise due to averaging of regions properties over their area. The watershed segmentation technique is based on interpretation of an image as a topographic relief and on simulation of flow of water along steepest descent paths called downstreams. Thus, for each local minimum of the image, a drainage region is defined, which, if computed for a gradient image, represents an area with approximately constant properties. The segmentation technique is further extended for multi-scale image analysis by means of Gaussian smoothing. The aim of smoothing is to suppress image details that are smaller than standard deviation of the Gaussian. However, smoothing results not only in the desired increase of region size, but it also affects position of region boundaries, at least for larger standard deviations of the Gaussian filter. Therefore a new technique is proposed, based on region hierarchies, which enables to transfer region contours with precise position from the levels with low smoothing to levels with higher smoothing. Thus, segmentation of an image into large regions, but with exact contours, is obtained.
Źródło:
Journal of Medical Informatics & Technologies; 2002, 3; MI161-169
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The f3d tools for processing and visualization of volumetric data
Autorzy:
Šrámek, M.
Dimitrov, L. I.
Straka, M.
Červeňanský, M.
Powiązania:
https://bibliotekanauki.pl/articles/333554.pdf
Data publikacji:
2004
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
przetwarzanie danych w 3D
wizualizacja objętości
format pliku 3D
3D data processing
volume visualization
Opis:
In this paper we introduce the f3d format for storage of volumetric data together with a suite of tools for processing, segmentation and visualization of such data. Both the format and tools were developed for a highly variable and rapidly evolving academic environment, where new data processing and visualization tasks emerge very often. The tools address all the steps of a volume visualization pipeline: starting with import of external formats, over preprocessing, filtering, segmentation to interactive visualization.
Źródło:
Journal of Medical Informatics & Technologies; 2004, 7; MIP69-78
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
3D watershed transform combined with a probabilistic atlas for medical image segmentation
Autorzy:
Straka, M.
La Cruz, A.
Kochl, A.
Sramek, M.
Groller, E.
Fleischmann, D.
Powiązania:
https://bibliotekanauki.pl/articles/333997.pdf
Data publikacji:
2003
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
angiografia tomografii komputerowej
segmentacja oparta na wiedzy
probabilistyczny atlas
kategoria histogramu
CT angiography
knowledge based segmentation
probabilistic atlas
thin-plate-spline
histogram classification
Opis:
Recent advances in medical imaging technology using multiple detector-row computed tomography (CT) provide volumetric datasets with unprecedented spatial resolution. This has allowed for CT to evolve into an excellent non-invasive vascular imaging technology, commonly referred to as CT-angiography. Visualisation of vascular structures from CT datasets is demanding, however, and identification of anatomic objects in CT-datasets is highly desirable. Density and/or gradient operators have been used most commonly to classify CT data. In CT angiography, simple density/gradient operators do not allow precise and reliable classification of tissues due to the fact that different tissues (e.g. bones and vessels) possess the same density range and may lie in close spatial vicinity. We think, that anatomic classification can be achieved more accurately, if both spatial location and density properties of volume data are taken into account. We present a combination of two well-known methods for volume data processing to obtain accurate tissue classification. 3D watershed transform is used to partition the volume data in morphologically consistent blocks and a probabilistic anatomic atlas is used to distinguish between different kinds of tissues based on their density.
Źródło:
Journal of Medical Informatics & Technologies; 2003, 6; IT69-78
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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