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29 March 2016 The 3D EdgeRunner Pipeline: a novel shape-based analysis for neoplasms characterization
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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.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fernando Yepes-C, Rebecca Johnson, Yi Lao, Darryl Hwang, Julie Coloigner, Felix Yap, Desai Bushan, Phillip Cheng, Inderbir Gill, Vinay Duddalwar, and Natasha Lepore "The 3D EdgeRunner Pipeline: a novel shape-based analysis for neoplasms characterization", Proc. SPIE 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging, 97882N (29 March 2016);

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