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Abstract #2661

Automated Segmentation of Ewing’s Sarcoma using Diffusion Weighted Imaging

Amit Mehndiratta1,2, 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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