Meeting Banner
Abstract #3429

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

Snekha Thakran1, Subhajit Chatterjee1,2,3, Rakesh Kumar Gupta4, and Anup Singh1,5

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.

This abstract and the presentation materials are available to members only; a login is required.

Join Here