TY - JOUR
KW - Cancer
KW - Machine Learning
KW - Neural Network
KW - Medicine
AU - Mansour Esmaeilpour
AU - Elham Gohariyan
AU - Mohammad Mehdi Shirmohammadi
AB - Breast cancer is one of the common cancers among women so that early diagnosing of it can effectively help its treatment in this study, considering combination of Mammography and MRI pictures, we will try to recognize glands in existing pictures which identify all around of gland complete and precisely and separate it completely. In this method using artificial intelligence algorithm such as Affine transformation, Gabor filter, neural network, and support vector machine, image analysis will be carried out. The accuracy of proposed method is 98.14. In this work a special framework is presented which simplifies cancer diagnosis. The algorithm of proposed method is tested on z16 images. High speed and lack of human error are the most important factors in proposed intelligent system.
IS - Special Issue on 3D Medicine and Artificial Intelligence
M1 - 5
N2 - Breast cancer is one of the common cancers among women so that early diagnosing of it can effectively help its treatment in this study, considering combination of Mammography and MRI pictures, we will try to recognize glands in existing pictures which identify all around of gland complete and precisely and separate it completely. In this method using artificial intelligence algorithm such as Affine transformation, Gabor filter, neural network, and support vector machine, image analysis will be carried out. The accuracy of proposed method is 98.14. In this work a special framework is presented which simplifies cancer diagnosis. The algorithm of proposed method is tested on z16 images. High speed and lack of human error are the most important factors in proposed intelligent system.
PY - 2017
SP - 20
EP - 24
T2 - International Journal of Interactive Multimedia and Artificial Intelligence
TI - The Combination of Mammography and MRI for Diagnosing Breast Cancer Using Fuzzy NN and SVM
UR - http://www.ijimai.org/journal/sites/default/files/files/2016/12/ijimai20174_5_3_pdf_18248.pdf
VL - 4
SN - 1989-1660
ER -