Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Publication Type : Book Chapter
Publisher : Optimizing Assistive Technologies for Aging Populations, IGI Global,
Source : Optimizing Assistive Technologies for Aging Populations, IGI Global, p.378–395 (2015)
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Center : Center for Computational Engineering and Networking
Department : Center for Computational Engineering and Networking (CEN), Computer Science
Year : 2015
Abstract : Management of breast cancer in elder patients is challenging due to a lack of good quality evidence regarding the role of adjuvant chemotherapy. Mammograms can depict most of the significant changes of breast disease. The primary radiographic signs of breast cancer are masses (its density, site, shape, borders), spicular lesions and calcification content. The basic idea is to convert the mammogram image and convert into 3-D matrix. Obtained matrix is used to convert the mammogram into binary image. Several techniques like detecting cell, filling gaps, dilating gaps, removing border, smoothing the objects, finding structures & extracting large objects have been used. Finally finding the granulometry of tissues in an Image without explicitly segmenting (detecting) each object. Compared to existing multiscale enhancement approaches, images processed with this method appear more familiar to radiologists and naturally close to the original mammogram.
Cite this Research Publication : A. Kumar Wadhwani, Wadhwani, S., and Dr. Tripty Singh, “Computer Aided Diagnosis System for Breast Cancer Detection”, in Optimizing Assistive Technologies for Aging Populations, IGI Global, 2015, pp. 378–395.