Abstract #3429

Feature Extraction and Analysis for Characterization of Breast Lesion Type using Multi-parametric MRI

Snekha Thakran¹, Subhajit Chatterjee^1,2,3, Rakesh Kumar Gupta⁴, and Anup Singh^1,5

¹Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India, ²C-DOT India, New Delhi, India, ³Computer Science and Engineering, Indian Institute of Technology Delhi, New Delhi, India, ⁴Department of Radiology and Imaging, Fortis Memorial Research Institute, Gurgaon, India, New Delhi, India, ⁵Department of Biomedical Engineering, All India Institute of Medical Sciences Delhi, New Delhi, India

Quantitative analysis of T₁-perfusion data provides estimation of hemodynamic and physiological parameters of tissue. Texture analysis uses mathematical approach to distinguish the spatial distribution of signal intensity variations. In this study, we computed different texture and quantitative parameters in terms of characterizing histological types (lobular and ductal) of invasive breast cancer. Experimental results revealed that combination of texture and quantitative features provided highest sensitivity and specificity to differentiate IDC and ILC breast lesions.

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