ELCVIA

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ELCVIA	5 records found	Search took 0.01 seconds.

16 p, 1.4 MB

Comprehensive analysis of high-performance computing methods for filtered back-projection / Mendl, Christian B. (Technische Universität München) ; Eliuk, Steven (University of Alberta. Department of Radiology and Diagnostic Imaging) ; Noga, Michelle (University of Alberta. Servier Virtual Cardiac Centre) ; Boulanger, Pierre (University of Alberta. Department of Radiology and Diagnostic Imaging)
This paper provides an extensive runtime, accuracy, and noise analysis of Computed To-mography (CT) reconstruction algorithms using various High-Performance Computing (HPC) frameworks such as: "conventional" multi-core, multi threaded CPUs, Compute Unified Device Architecture (CUDA), and DirectX or OpenGL graphics pipeline programming. [...]
2013 - DOI (Digital Object Identifier)

10.5565/rev/elcvia.508
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 12, Núm. 1 (2013) , p. 1-16

Detailed record -

16 p, 11.3 MB

Perceptual Color Image Smoothing via a New Region-Based PDE Scheme / Magnier, Baptiste (Ecole des Mines d'Ales (Nimes, França). LGi2P) ; Montesinos, Philippe (Ecole des Mines d'Ales (Nimes, França). LGi2P) ; Diep, Daniel (Ecole des Mines d'Ales (Nimes, França). LGi2P)
In this paper, we present a new color image regularization method using a rotating smoothing filter. This approach combines a pixel classification method, which roughly determines if a pixel belongs to a homogenous region or an edge with an anisotropic perceptual edge detector capable of computing two precise diffusion directions. [...]
2013 - DOI (Digital Object Identifier)

10.5565/rev/elcvia.509
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 12, Núm. 1 (2013) , p. 17-32

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9 p, 422.9 KB

An Automatic Ship Detection Method Based on Local Gray-Level Gathering Characteristics in SAR Imagery / XiaoLong, Wang (Chinese Academy of Sciences. Institute of Electronics) ; CuiXia, Chen (Chinese Academy of Sciences. Institute of Biophysics)
This paper proposes an automatic ship detection method based on gray-level gathering characteristics of synthetic aperture radar (SAR) imagery. The method does not require any prior knowledge about ships and background observation. [...]
2013 - DOI (Digital Object Identifier)

10.5565/rev/elcvia.528
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 12, Núm. 1 (2013) , p. 33-41

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15 p, 671.5 KB

Alzheimer's disease early detection from sparse data using brain importance maps / Kodewitz, Andreas ; Lelandais, Sylvie ; Montagne, Christophe ; Vigneron, Vincent ; University of Evry. IBISC Laboratory
Statistical methods are increasingly used in the analysis of FDG-PET images for the early diagnosis of Alzheimer's disease. We will present a method to extract information about the location of metabolic changes induced by Alzheimer's disease based on a machine learning approach that directly links features and brain areas to search for regions of interest (ROIs). [...]
2013 - DOI (Digital Object Identifier)

10.5565/rev/elcvia.531
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 12, Núm. 1 (2013) , p. 42-56

Detailed record -

28 p, 2.2 MB

Peak Trekking of Hierarchy Mountain for the Detection of Cerebral Aneurysm using Modified Hough Circle Transform / Mitra, Jubin (Bengal Engineering and Science University (Howrah, Índia). Department of Electronics & Telecommunication Engineering) ; Chandra, Abhijit (Bengal Engineering and Science University (Howrah, Índia). Department of Electronics & Telecommunication Engineering) ; Halder, Tanmay (Bengal Engineering and Science University (Howrah, Índia). Department of Electronics & Telecommunication Engineering)
The Circle of Willis is in the junction of two carotid arteries and two vertebral arteries that supply the brain with nutrition. Junctions where these arteries come together may develop weak spots that can balloon out and fill with blood, creating aneurysms. [...]
2013 - DOI (Digital Object Identifier)

10.5565/rev/elcvia.529
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 12, Núm. 1 (2013) , p. 57-84

Detailed record -

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