Publication Type : Conference Paper
Publisher : Springer
Source : International Conference On Innovative Computing And Communication, pp. 225-241. Singapore: Springer Nature Singapore, 2023
Url : https://link.springer.com/chapter/10.1007/978-981-99-3315-0_18
Campus : Chennai
School : School of Engineering
Department : Electronics and Communication
Year : 2023
Abstract : This paper discusses the categorisation of breast cancer based on mammography images—MLO perspective. This research presents a method for finding malignant tumours in mammography images utilising the Gabor cut algorithm for region of interest from the morphologically upgraded image for cancer detection with better detection rate and accuracy. To eliminate spurious matching points, the features were examined using the enhanced feature extraction technique. The improved ORB method with RANSAC implementation is utilised in this work to extract the necessary features by masking the background data. The methods offered provide characteristics with exact information about cancerous tissues. This automated extraction has a 98.006% accuracy
Cite this Research Publication : Saranyaraj, D., R. Vaisshale, and R. NandhaKishore. "Region of Interest and Feature-based Analysis to Detect Breast Cancer from a Mammogram Image." In International Conference On Innovative Computing And Communication, pp. 225-241. Singapore: Springer Nature Singapore, 2023