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Abstract #1117

Characterization of Breast Tumor using Machine Learning based upon Multi-parametric MRI Features.

Snekha Thakran1, Rakesh Kumar Gupta2, and Anup Singh1,3
1Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India, Delhi, India, 2Department of Radiology, Fortis Memorial Research Institute, Haryana, Gurgaon, India, Delhi, India, 3Department of Biomedical Engineering, All India Institute of Medical Science, New Delhi, India, Delhi, India

Multi-parametric MRI(mp-MRI) has shown promising outcomes with high sensitivity and accuracy in the characterization of breast tumor. Quantitative analysis of mp-MRI and texture features with machine learning approach have also shown potential in improving accuracy of breast tumor classification. The objective of this study was to differentiate low-grade vs. high-grade breast tumor using machine learning with optimized feature vector obtained from mp-MRI data. The study included mp-MRI data of 35 patients with breast cancer. The combination of support-vector-machine(SVM) with Wrapper method using Adaptive-Boosting(AdaBoost) technique resulted in high sensitivity(0.94±0.07), specificity(0.80±0.05), and accuracy(0.90±5.48) in classification of low-grade vs. high-grade tumors.

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