| Literature DB >> 31178623 |
Fernando Yepes-C1, Rebecca Johnson2, Darryl Hwang3, Julie Coloigner1, Felix Yap3, Desai Bushan3, Phillip Cheng3, Inderbir Gill4, Vinay Duddalwar3, Natasha Lepore2,1.
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.Entities:
Keywords: Computer Aided Diagnostics; EdgeRunner Pipeline; Image Processing; Tumor Shape Analysis
Year: 2016 PMID: 31178623 PMCID: PMC6554207 DOI: 10.1117/12.2217238
Source DB: PubMed Journal: Proc SPIE Int Soc Opt Eng ISSN: 0277-786X