References
[1]. Ashkan Tashk, Mohammad Sadegh Helfroush,
Habibollah Danyali, and Mojgan Akbarzadeh-Jahromi,
(2015). “Automatic detection of breast cancer mitotic
cells based on the combination of textural, statistical and
innovative mathematical features”. http://dx.doi.org/
10.1016/ j.apm.2015.01.051
[2]. Chien-Shun Lo and Chuin-Mu Wang, (2012). “Support
Vector Machine for breast MR image classification”.
Computers and Mathematics with Applications, Vol.64,
pp.1153-1162. doi:10.1016/j.camwa.2012.03.033
[3]. Defeng Wang, Lin Shi, and Pheng Ann Heng, (2009).
“Automatic detection of breast cancers in
mammograms using structured Support Vector
Machines”. Neurocomputing, Vol.72, pp.3296-3302.
doi:10.1016/j. neucom.2009.02.015
[4]. Betsabeh Tanoori, Zohreh Azimifar, Alireza
Shakibafar, and Sarajodin Katebi, (2011). “Brain
volumetry : An active contour model-based
segmentation followed by SVM-based classification”.
Computers in Biology and Medicine, Vol.41, pp.619-632.
doi:10.1016/j. compbiomed.2011.05.013.
[5]. Hong-Ying Yang, Xiang-Yang Wang, Qin-Yan Wang, and Xian-Jin Zhang, (2012). “LS-SVM based image
segmentation using color and texture information”. J. Vis.
Commun. Image, Vol.23, pp.1095-1112. http://dx.doi.
org/10.1016/j.jvcir.2012.07.007
[6]. Mohsen Keshani, Zohreh Azimifar, Farshad Tajeripour,
and Reza Boostani, (2013). “Lung nodule segmentation
and recognition using SVM classifier and active contour
modeling: A complete intelligent system”. Computers in
B i o l o g y and Medicine , Vol. 43, pp. 287-30 .
http://dx.doi.org/10.1016/j.compbiomed.2012.12.004
[7]. Teresa Wu, Min Hyeok Bae, Min Zhang, Rong Pan,
and Alexandra Badea, (2012). “A prior feature SVM-MRF
based method for mouse brain segmentation”.
NeuroImage, Vol.59, pp.2298-2306. doi:10.1016/
j.neuroimage. 2011.09.053
[8]. Xiang-Yang Wang, Qin-Yan Wang, Hong-Ying Yang,
Juan Bu, (2011). “Color image segmentation using
automatic pixel classification with Support Vector
Machine”. Neurocomputing, Vol.74, pp.388-3911.
doi:10.1016/j.neucom.2011.08.004
[9]. Ye Chen, Judd Storrs, Lirong Tan, Lawrence J.
Mazlack, Jing-Huei Lee, and Long J. Lu, (2014).
“Detecting brain structural changes as biomarker from
magnetic resonance images using a local feature based
SVM approach”. Journal of Neuroscience Methods,
Vol.221, pp.22-31.
[10]. Wener Borges Sampaio, Edgar Moraes Diniz, Aristo
fanes Correa Silva, Anselmo Cardoso de Paiva, and
Marcelo Gattass, (2011). “Detection of masses in
mammogram images using CNN, geostatistic functions
and SVM”. Computers in Biology and Medicine, Vol.41,
pp.653-664. doi:10.1016/j.compbiomed.2011.05.017
[11]. Mohamed Meselhy Eltoukhy, Ibrahima Faye, and
Brahim Belhaouari Samir, (2010). “A comparison of
wavelet and curvelet for breast cancer diagnosis in digital
mammogram”. Computers in Biology and Medicine,
Vol.40, pp.384-391. doi:10.1016/j.compbiomed.
2010.02.002
[12]. Fatemeh Moayedi, Zohreh Azimifar, Reza Boostani,
and Serajodin Katebi, (2010). “Contourlet-based
mammography mass classification using the SVM family”. Computers in Biology and Medicine, Vol.40,
pp.373-383. doi:10.1016/j.compbiomed.2009.12.006
[13]. Shichong Zhou, Jun Shi, Jie Zhu, Yin Cai, and Ruiling
Wang, (2013). “Shearlet-based texture feature extraction
for classification of breast tumor in ultrasound”.
Biomedical Signal Processing and Control, Vol.8, pp.688-
696. http://dx.doi.org/10.1016/j.bspc.2013.06.011
[14]. V. Vapnik, (2000). The Nature of Statistical Learning
Theory, Spring-Verlag, New York.
[15]. Cortes, C. and V. Vapnik, (1995). “Support vector
networks”. Machine Learning, Vol.20, No.3, pp.273-297.
[16]. Stavros AT, Thickman D, Rapp CL, Dennis MA, Parker
SH, and Sisney GA, (1995). “Solid breast nodules: Use of
sonography to distinguish between benign and
malignant lesions”. Radiology, Vol.196, pp.123-134.
[17]. Jawad Nagi, Sameem Abdul Kareem, Farrukh Nagi,
and Syed Khaleel Ahmed (2010). “Automated Breast
Profile Segmentation for ROI Detection Using Digital
Mammograms”. 2010 IEEE EMBS Conference on
Biomedical Engineering & Sciences (IECBES 2010), Kuala
Lumpur, Malaysia, pp.87-99.
[18]. R. Ramani, (2013). “The Pre-Processing Techniques for Breast Cancer Detection in Mammography Images”.
I.J. Image, Graphics and Signal Processing, pp.47-54.
[19]. D. Sujitha Priya, (2013). “Breast Cancer Detection In
Mammogram Images Using Region-Growing And
Contour Based Segmentation Techniques”. International
Journal of Computer & Organization Trends, Vol.3, No.8,
ISSN: 2249.
[20]. Jawad Nagi,and Sameem, (2010). “Automated
Breast Profile Segmentation for ROI Detection Using Digital
Mammograms”. 2010 IEEE EMBS Conference on
Biomedical Engineering & Sciences (IECBES 2010), Kuala
Lumpur, Malaysia.
