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Wavelets for Computer-Aided Diagnosis in Radiographic Images

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Wavelets in Signal and Image Analysis

Part of the book series: Computational Imaging and Vision ((CIVI,volume 19))

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Abstract

Computer-vision techniques based on wavelets are presented with applications to computer-aided diagnosis (CAD) in medical images. CAD is a method for assisting radiologists’ interpretation of medical images. CAD schemes act as a second reader and alert radiologists to suspicious lesions. Development of CAD schemes is an active area of research, motivated by the fact that radiologists tend to misdiagnose cancerous lesions in medical images. In the past several years, we have been extensively developing wavelet-based techniques for CAD schemes. Development of these techniques has led to a new CAD scheme and has yielded significant improvements in the performance of the existing CAD schemes. This chapter describes two wavelet-based, low-level computer vision techniques: simultaneous segmentation and registration, and matching pursuit with optimally weighted wavelet packets. We present their application to the computer-aided detection of lung nodules in chest radiographs and microcalcifications in mammograms.

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Author information

Authors and Affiliations

  1. Department of Radiology, The University of Chicago, Chicago, IL, 60637, USA

    Hiroyuki Yoshida

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  1. Hiroyuki Yoshida
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Editor information

Editors and Affiliations

  1. Texas Tech University, Lubbock, Texas, USA

    Arthur A. Petrosian

  2. University of Colorado, Boulder, Colorado, USA

    François G. Meyer

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© 2001 Springer Science+Business Media Dordrecht

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Yoshida, H. (2001). Wavelets for Computer-Aided Diagnosis in Radiographic Images. In: Petrosian, A.A., Meyer, F.G. (eds) Wavelets in Signal and Image Analysis. Computational Imaging and Vision, vol 19. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9715-9_14

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  • DOI: https://doi.org/10.1007/978-94-015-9715-9_14

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-5838-6

  • Online ISBN: 978-94-015-9715-9

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