Kenichi Yokoyama7
Toshiaki Nitatori7
Masamichi Imai4
7Kenichi Yokoyama
7Toshiaki Nitatori
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In this paper, we propose a novel feature localization method based on a global vector concentration approach. Our approach does not rely on the detection of local salient features around feature points. Instead, we exploit global structural information of the object extracted by calculating the concentration of directional vectors from sampling points.(More)
A method for three dimensional object recognition based on depth image information is proposed. A depth aspect image is defined as an orientation standardized appearance from the original depth data of the object, which is transformed by the rigid transformation drawn by each possible basis pair of every three feature points of the object depth data. They(More)
PURPOSE For accurate evaluation of myocardial perfusion on computed tomography images, precise identification of the myocardial borders of the left ventricle (LV) is mandatory. In this article, we propose a method to detect the contour of LV myocardium automatically and accurately. METHODS Our detection method is based on active shape model. For precise(More)
OBJECTIVES Automatic slice alignment is important for easier operation and shorter examination times in cardiac magnetic resonance imaging (MRI) examinations. We propose a new automatic slice alignment method for six cardiac planes (short-axis, vertical long-axis, horizontal long-axis, 4-chamber, 2-chamber, and 3-chamber views). MATERIALS AND METHODS(More)