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Abstract #1545

Superpixels-based Segmentation and Automated Identification of Active Tumour and Necrotic regions in Bone Tumor using T1 and Diffusion Weighted Imaging

Amit Mehndiratta1, Esha Baidya Kayal1, Sneha Patil Kulkarni1, Raju Sharma2, Devasenathipathy Kandasamy2, and Sameer Bakhshi3

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

Proper Delineation of the tumour boundary and assessment of tumour size can take crucial part in treatment planning and monitoring treatment response. We investigate a fully automated Simple linear iterative clustering (SLIC) superpixel-based method for detection and segmentation of pathological tissues like oedema, tumour and necrosis associated with Osteosarcoma. Experimental results provide a close match to expert delineation and was able to estimate areas of active tumor and necrosis with good accuracy.

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