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Breast cancer diagnosis in digital mammogram using multiscale curvelet transform

✍ Scribed by Mohamed Meselhy Eltoukhy; Ibrahima Faye; Brahim Belhaouari Samir

Publisher: Elsevier Science
Year: 2010
Tongue: English
Weight: 616 KB
Volume: 34
Category: Article
ISSN: 0895-6111
DOI: 10.1016/j.compmedimag.2009.11.002

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✦ Synopsis

This paper presents an approach for breast cancer diagnosis in digital mammogram using curvelet transform. After decomposing the mammogram images in curvelet basis, a special set of the biggest coefficients is extracted as feature vector. The Euclidean distance is then used to construct a supervised classifier. The experimental results gave a 98.59% classification accuracy rate, which indicate that curvelet transformation is a promising tool for analysis and classification of digital mammograms.

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