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Abstract #3554

Segmentation of Contrast Enhancing Brain Tumor Region using a Machine Learning Framework based upon Pre and Post contrast MR Images

Neha Vats1, Virendra Kumar Yadav1, Manish Awasthi1, Dinil Sasi1, Mamta Gupta2, Rakesh Kumar Gupta2, and Anup Singh1,3
1Centre for Biomedical Engineering, Indian Institute of Technology, Delhi, New Delhi, India, 2Department of Radiology, Fortis Memorial Research Institute, Gurugram, India, 3Biomedical Engineering, AIIMS, New Delhi, India

Segmentation of contrast enhancing tumor region from post-contrast T1-W MR images is sometime difficult due to low enhancement or presence of infarct tissue around or inside tumor, which exhibits similar intensity as contrast enhancement. Relative difference map obtained from pre-and post-contrast T1-weighted images can increase sensitivity to enhancement visualization as well as clearly differentiate infarct tissue from enhancing lesion. The objective of the current study was to evaluate accuracy of segmentation of contrast enhancing lesion using Support Vector Machine (SVM) classifier developed on relative difference map intensities. Optimized SVM classifier enabled accurate segmentation of contrast enhancing tumor lesion.

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