DocumentCode
250012
Title
Mammography Feature Analysis and Mass Detection in Breast Cancer Images
Author
Patel, Bhagwati Charan ; Sinha, G.R.
Author_Institution
Dept. of Inf. Technol., Shri Shankaracharya Group of Instn., Bhilai, India
fYear
2014
fDate
9-11 Jan. 2014
Firstpage
474
Lastpage
478
Abstract
This paper introduces a novel approach for accomplishing mammographic feature analysis through detection of tumor, in terms of their size and shape with experimental work for early breast tumor detection. The objective is to detect the abnormal tumor/tissue inside breast tissues using three stages: Preprocessing, Segmentation and post processing stage. By using preprocessing noise are remove and than segmentation is applied to detect the mass, after that post processing is applied to find out the benign and malignant tissue with the affected area in the cancers breast image. Size of tumor is also detected in these steps. The occurrences of cancer nodules are identified clearly. Compared with an expert observer reading the Mammography, our algorithm achieves 96.5% sensitivity, 89% specificity, 95.6% accuracy value.
Keywords
biological organs; cancer; feature extraction; image denoising; image segmentation; mammography; medical image processing; tumours; accuracy; benign tissue; breast cancer images; image post processing; image preprocessing; image segmentation; malignant tissue; mammography feature analysis; mass detection; noise removal; sensitivity; specificity; tumor detection; Accuracy; Breast cancer; Feature extraction; Image segmentation; Lesions; accuracy; breast cancer; mammography image; segmentation; sensitivity; specificity; tumor;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronic Systems, Signal Processing and Computing Technologies (ICESC), 2014 International Conference on
Conference_Location
Nagpur
Type
conf
DOI
10.1109/ICESC.2014.89
Filename
6745425
Link To Document