Abstract
Image analysis is a rapidly evolving and increasingly utilized tool in histology. It enables high throughput analysis of a large number of samples, offering the potential for increased precision, plus reduced workload for researchers. The ability of slide scanners to create high resolution whole slide images (WSI) of tissue sections gives rise to the need for quick and effective identification of areas of interest within these images. This review focuses on the use of Aperio GENIE, from Leica Biosystems, as an image analysis tool for automatic identification of different tissue morphologies and cell cohorts within WSI.
Introduction
Aperio GENIE is a general purpose, interactive, adaptive tool for automatically finding and classifying regions of interest (ROIs), such as tumor regions, in heterogenous tissue across large numbers of digital slide images. Instead of manually annotating areas of interest in all digital images, Aperio GENIE allows users to annotate a few representative contrasting areas within a slide set, which can be used as a training set. The training set is used as a reference by the algorithm to detect and distinguish these areas within the rest of the slides. Combined with other quantitative image analysis tools, Aperio GENIE enables highly automated whole slide analysis of immunohistochemistry (IHC) or in situ hybridization (ISH) staining in tumor areas (e.g. in entire tissue sections across large sets of slides).
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