Paper
17 March 2008 A new registration method with voxel-matching technique for temporal subtraction images
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Abstract
A temporal subtraction image, which is obtained by subtraction of a previous image from a current one, can be used for enhancing interval changes on medical images by removing most of normal structures. One of the important problems in temporal subtraction is that subtraction images commonly include artifacts created by slight differences in the size, shape, and/or location of anatomical structures. In this paper, we developed a new registration method with voxel-matching technique for substantially removing the subtraction artifacts on the temporal subtraction image obtained from multiple-detector computed tomography (MDCT). With this technique, the voxel value in a warped (or non-warped) previous image is replaced by a voxel value within a kernel, such as a small cube centered at a given location, which would be closest (identical or nearly equal) to the voxel value in the corresponding location in the current image. Our new method was examined on 16 clinical cases with MDCT images. Preliminary results indicated that interval changes on the subtraction images were enhanced considerably, with a substantial reduction of misregistration artifacts. The temporal subtraction images obtained by use of the voxel-matching technique would be very useful for radiologists in the detection of interval changes on MDCT images.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yoshinori Itai, Hyoungseop Kim, Seiji Ishikawa, Shigehiko Katsuragawa, and Kunio Doi "A new registration method with voxel-matching technique for temporal subtraction images", Proc. SPIE 6915, Medical Imaging 2008: Computer-Aided Diagnosis, 69153I (17 March 2008); https://doi.org/10.1117/12.769921
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CITATIONS
Cited by 9 scholarly publications and 1 patent.
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KEYWORDS
Lung

Computed tomography

Image registration

Image enhancement

3D image processing

Medical imaging

Image segmentation

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