"Differential cell counts using center-point networks achieves human-level accuracy and efficiency over segmentation"
Perth Machine Learning Group's first paper in collaboration with Telethon Kids Institute, The Data Institute, University of San Francisco, Center for Data and Computing (CDAC) at the University of Chicago and University of Newcastle NSW, has been published in Nature Scientific Reports.
Congratulations to Sarada Lee (李文華) GAICD and co-authors Andrew Shaw, David Uminsky, Luke Garratt and Jodie Simpson
The work addresses a key aspect of operationalizing computer vision workflows, through the efficient generation of supervised labels. This has broad application as a tool, outside of digital pathology, so great to see it published.
