Title:Performance Identification Using Morphological Approach on Digital Mammographic Images
VOLUME: 11 ISSUE: 2
Author(s):Karthick Subramanian and Sathiyasekar Kumarasamy
Affiliation:Department of Electrical and Electronics Engineering, The Kavery Engineering College, Mecheri, Salem District-636453, Tamil Nadu, India.
Keywords:Breast cancer, region growing algorithm, mammography, image segmentation, back propagation, feed forward
network, neural network.
Abstract:Background: Digital Mammography is the most vital and successful
imaging modality used by radio diagnosis method to find out breast cancer. Breast
cancer is the most significant and common cause of cancer death in women. The
main problem is to find the accurate and efficient method for breast cancer
segmentation.
Method: The morphological method is the most important approach in image
segmentation method. There are various new methods available for breast cancer
image segmentation but those methods are not upto the mark. They fall behind the
image segmentation.
Results: On comparing both the algorithms for segmenting the mammographic
images, applying the Neural Networks algorithm will be a better option rather than applying Region
Growing Algorithm. The accuracy of the segmentation is higher in the morphological image
segmentation approach.
Conclusion: The results show that, the performance of morphological approach is more efficient than
other methods.