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Proc SPIE Int Soc Opt Eng. 2016 Feb-Mar;9788. pii: 97882N. doi: 10.1117/12.2217238. Epub 2016 Mar 29.

The 3D EdgeRunner Pipeline: A Novel Shape-Based Analysis for Neoplasms Characterization.

Author information

1
Children's Hospital Los Angeles, 4650 Sunset Blvd, Los Angeles-CA, USA.
2
University of Southern California, 900 W 34th St, Los Angeles-CA, USA.
3
Dept of Radiology, Keck School of Medicine - USC, 1975 Zonal Av, Los Angeles-CA, USA.
4
Institute of Urology, USC, 1441 Eastlake Ave, Los Angeles-CA, USA.

Abstract

The characterization of tumors after being imaged is currently a qualitative process performed by skilled professionals. If we can aid their diagnosis by identifying quantifiable features associated with tumor classification, we may avoid invasive procedures such as biopsies and enhance efficiency. The aim of this paper is to describe the 3D EdgeRunner Pipeline which characterizes the shape of a tumor. Shape analysis is relevant as malignant tumors tend to be more lobular and benign ones tare generally more symmetrical. The method described considers the distance from each point on the edge of the tumor to the centre of a synthetically created field of view. The method then determines coordinates where the measured distances are rapidly changing (peaks) using a second derivative found by five point differentiation. The list of coordinates considered to be peaks can then be used as statistical data to compare tumors quantitatively. We have found this process effectively captures the peaks on a selection of kidney tumors.

KEYWORDS:

Computer Aided Diagnostics; EdgeRunner Pipeline; Image Processing; Tumor Shape Analysis

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