Title :
Another Approach to Detection of Abnormalities in MR-Images Using Support Vector Machines
Author :
Behnamghader, Ehsan ; Ardekani, Reza Dehestani ; Torabi, Meysam ; Fatemizadeh, Emad
Author_Institution :
Dept. of Electr. Eng., Sharif Univ. of Technol., Tehran, Iran
Abstract :
In this paper we will address two major problems in mammogram analysis for breast cancer in MR-images. The first is classification between normal and abnormal cases and then, discrimination between benign and malignant in cancerous cases. Our proposed method extracts textural and statistical descriptive features that are fed to a learning engine based on the use of support vector machine learning framework to categorize them. The obtained results show excellent accuracy in both classification problems, that proves the appropriate combination of our features and selecting powerful classifier i.e. Support Vector Machine leads us to a brilliant outcome.
Keywords :
biomedical MRI; cancer; feature extraction; image classification; image texture; mammography; medical image processing; support vector machines; tumours; MR images; abnormalities detection; benign tumours; cancer; feature extraction; image classification; image texture; malignant tumours; mammogram analysis; support vector machines; Artificial neural networks; Breast cancer; Data analysis; Diseases; Feature extraction; Machine learning; Mammography; Neural networks; Support vector machine classification; Support vector machines;
Conference_Titel :
Image and Signal Processing and Analysis, 2007. ISPA 2007. 5th International Symposium on
Conference_Location :
Istanbul
Print_ISBN :
978-953-184-116-0
DOI :
10.1109/ISPA.2007.4383671