Abstract
In this paper, we present a ROI (Region-Of-Interest)-based medical image retrieval system that is considering combination of feature descriptors and initial weights for similarity matching. For semantic ROI segmentation, we create attention window (AW) to remove the meaningless regions included in the image such as background and propose a quad-tree based ROI segmentation method. In addition, in order to improve the retrieval performance and consider human perception, initial weights for feature distances are also proposed. From, several experiments, we demonstrate that the ROI-based method having different initial weights shows the better performance than previous related methods.
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© 2006 Springer-Verlag Berlin Heidelberg
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Seo, M., Ko, B., Chung, H., Nam, J. (2006). ROI-Based Medical Image Retrieval Using Human-Perception and MPEG-7 Visual Descriptors. In: Sundaram, H., Naphade, M., Smith, J.R., Rui, Y. (eds) Image and Video Retrieval. CIVR 2006. Lecture Notes in Computer Science, vol 4071. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11788034_24
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DOI: https://doi.org/10.1007/11788034_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36018-6
Online ISBN: 978-3-540-36019-3
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