TY  - JOUR
N1  - cited By 110
SP  - 269
TI  - Breast cancer diagnosis in digital mammogram using multiscale curvelet transform
AV  - none
EP  - 276
SN  - 08956111
IS  - 4
N2  - 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. © 2009 Elsevier Ltd.
ID  - scholars1247
KW  - Breast cancer diagnosis; Curvelet transforms; Digital mammogram; Digital mammograms; Multi-resolutions
KW  -  Face recognition; Mammography; X ray screens
KW  -  Feature extraction
KW  -  article; breast cancer; cancer classification; cancer diagnosis; classifier; diagnostic accuracy; diagnostic procedure; digital mammography; human; image analysis; image processing; image reconstruction; priority journal
KW  -  Algorithms; Breast Neoplasms; Female; Humans; Mammography; Radiographic Image Enhancement; Radiographic Image Interpretation
KW  -  Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity
A1  - Eltoukhy, M.M.
A1  - Faye, I.
A1  - Samir, B.B.
JF  - Computerized Medical Imaging and Graphics
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-77952237386&doi=10.1016%2fj.compmedimag.2009.11.002&partnerID=40&md5=a52910c5505a38495d14c0838f0c5aa6
VL  - 34
Y1  - 2010///
ER  -