Abstract #2661

Automated Segmentation of Ewing’s Sarcoma using Diffusion Weighted Imaging

Amit Mehndiratta^1,2, Abhimanyu Sahai¹, Esha Baidya Kayal ¹, Jayendra Tiru Alampally³, Sameer Bakhshi⁴, Devasenathipathy K³, and Raju Sharma³

¹Center for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India, ²Department of Biomedical Engineering, All Indian Institute of Medical Sciences, New Delhi, India, ³Department of Radiology, All India Institute of Medical Sciences, New Delhi, India, ⁴BRA IRCH, All India Institute of Medical Sciences, New Delhi, India

Accurate demarcation of tumors on DWI MRimages could play a crucial role in diagnosis and prognosis when using quantitative image analysis like ADC or IVIM. Manual demarcation of tumour on each slice of a 3D stack is usually not feasible. Automated or semi-automated methods of segmentation are thus desirable specifically for DWimages that can be used to identify the tumor region, optimizing on both speed and accuracy. Our results reveals that semi-automated algorithms based on both Otsu-threshold or Active-Contours based region growing perform tumour segmentation with acceptable level of accuracy in diffusion MRimages and reduce time and manual effort required.

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