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Digital pathology has long been synonymous with the digitization of histology (tissue-based) samples. Liquid-based samples, however, are notoriously difficult to scan, as the objects of interest are suspended at different focal depths and can be sparse, which makes focusing a challenging task for scanners. Hamamatsu has just announced their partnership with Techcyte where we are using their API to apply computer vision and machine learning to improve the way the scanners focus on liquid-based cytological samples, and better choose regions of interest, which enables us to reduce scanned image file sizes.

Read the full press release (PR Newswire)