DocumentCode :
3253039
Title :
Classification of malignant tumors using multiple sonographic features
Author :
Chatterjee, Subarna ; Ray, Ajoy Kumar ; Karim, Rezaul ; Biswas, Arindam
Author_Institution :
Dept. of IT, Bengal Eng. & Sci. Univ., Howrah, India
fYear :
2011
fDate :
21-23 Dec. 2011
Firstpage :
252
Lastpage :
256
Abstract :
Breast cancer is the most common form of cancer among women and the second one in the world trailing behind lung cancer. In this paper, we present a diagnostic algorithm that uses multiple features of ultra-sonography for identifying breast nodule malignancy to provide better chance of a proper treatment. An artificial neural network has been put into operation in the form of multilayer perceptron to generate the predictive model. MATLAB has been used for the simulation of this algorithm and the results obtained are presented in this paper.
Keywords :
biomedical ultrasonics; cancer; image classification; medical image processing; multilayer perceptrons; patient diagnosis; tumours; MATLAB; artificial neural network; breast cancer; breast nodule malignancy; diagnostic algorithm; lung cancer; malignant tumor classification; multilayer perceptron; multiple sonographic features; predictive model; ultrasonography; Breast; Cancer; Feature extraction; Indexes; Lesions; Ultrasonic imaging; Breast; Medical diagnosis; Sono-Mammogram; Ultrasound(US); lobulations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Recent Trends in Information Systems (ReTIS), 2011 International Conference on
Conference_Location :
Kolkata
Print_ISBN :
978-1-4577-0790-2
Type :
conf
DOI :
10.1109/ReTIS.2011.6146877
Filename :
6146877
Link To Document :
بازگشت