TL;DR: A generic algorithm for spheroid segmentation that can be particularised in several ways
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Abstract: Spheroids are the most widely used 3D models for studying the effects of different micro-environmental characteristics on tumour behaviour, and for testing different preclinical and clinical treatments. In order to speed up the study of spheroids, imaging methods that automatically segment and measure spheroids are instrumental; and, several approaches for automatic segmentation of spheroid images exist in the literature. However, those methods fail to generalise to a diversity of experimental conditions. In this work, we tackle this problem by developing a generic segmentation algorithm that can be easily adapted to different scenarios. The feasibility of applying our approach has been tested with several datasets of spheroid images where the spheroids were grown under several experimental conditions, and the images acquired using different equipment. In order to facilitate the dissemination and use of our method, we have implemented it in an open-source tool called SpheroidJ that has been released in the form of an ImageJ plugin and a standalone application.
Keywords: Segmentation, Spheroid, ImageJ, Java
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