• Title/Summary/Keyword: SFR 측정방법

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Research for Bit-depth Conversion Development by Detection Lost Information to Resizing Process for Digital Photography (디지털 사진영상의 크기조절과정에서 유실되는 정보를 이용한 비트심도의 확장)

  • Cho, Do-Hee;Maik, Vivek;Paik, Joon-Ki;Har, Dong-Hwan
    • The Journal of the Korea Contents Association
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    • v.9 no.4
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    • pp.189-197
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    • 2009
  • A digital image usually has 8 bits of depth basically representing pixel intensity ranging for [0 255]. These pixel range allow 256 step levels of pixel values in the image. Thus the greyscale value for a given image is an integer. When we carry out interpolation of a given image for resizing we have to round the interpolated value to integer which can result in loss of quality on perceived color values. This paper proposes a new method for recovering this loss of information during interpolation process. By using the proposed method the pixels tend to regain more original values which yields better looking images on resizing.

A Study on the Minimization of Spatial Error in 3-Demensional Neuronavigator (3차원 영상지원 뇌수술장비의 공간오차 최소화에 관한 연구)

  • 이동준;다영신;이정교
    • Progress in Medical Physics
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    • v.8 no.2
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    • pp.19-26
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    • 1997
  • 3-dimensional Neuronavigator, Viewing Wand(ISG Technologies, Toronto, Cannda) is the surgery aid equipment for real time image (CT or MRI) guided surgery. The assurance of spatial accuracy of this system is important for clinical application. In this study, we have designed the acrylic brain phantom and measured the spatial error with that phantom. The phantom has designed to have capability to simulate image guided surgery. The phantom has 22 vertical rods whose diameters are 5mm and each rods has different length. CT scans were performed by 2.0mm slice and reconstructed for 3-Dimensional analysis. End point of rods can be obtained using reconstructed 3- Dimensional images and they are compared to actual position data. Average deviation was less than 2mm for various situations. Spatial error of Viewing Wand is acceptable in the clinical points of view, while cosmetics of the software needs to be modified to more user friend. Better accuracy can be expected when we apply the mixed fiducial fit registration and surface fit registration method. And even better results can be obtained if registration points distributed even and symetric around the target.

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