Comparative analysis of proficiencies of various textures and geometric features in breast mass classification using k-nearest neighbor

• Published in: Visual computing for industry, biomedicine and art Vol. 5; no. 1; pp. 3 - 19
• Main Authors: Singh, Harmandeep, Sharma, Vipul, Singh, Damanpreet
• Format: Journal Article
• Language: English
• Published: Singapore Springer Singapore 12.01.2022; Springer Nature B.V; SpringerOpen
• Subjects: Algorithms; Breast cancer; CAE) and Design; Classification; Classifiers; Comparative analysis; Computer Graphics; Computer Imaging; Computer Science; Computer-Aided Engineering (CAD; Correlation coefficients; Decision trees; Digital imaging; Feature selection; Image Processing and Computer Vision; Machine learning; Mammography; Media Design; Original; Original Article; Pattern Recognition and Graphics; Sensitivity; Support vector machines; Variance analysis; Vision; Mammography; Breast cancer; Machine learning; Classification

This paper introduces a comparative analysis of the proficiencies of various textures and geometric features in the diagnosis of breast masses on mammograms. An improved machine learning-based framework was developed for this study. The proposed system was tested using 106 full field digital mammogr...