Are you getting the maximum out of your sample images?
In this webinar, Joseph Daniele Ph.D. will demonstrate the power of deep learning to investigate and quantify variability within a cell.
Determining mitotic activity is a common component of many tumor grading systems but relies on tedious identification and enumeration of mitotic figures within selected fields of view. Using Visiopharm’s deep learning module, Joe and his group have trained a classifier to automatically identify and count a range of mitotic figure morphologies in an entire tissue sample.
Dr. Daniele received his Ph.D. in Biochemistry from Harvard, focusing on protein trafficking and axonal transport of the oncogenic mediator Hedgehog. He then proceeded to Andrew Dillin’s lab at UC-Berkeley where his research focused on high-content analysis and characterization of the unfolded protein response.
Branden recently joined Visiopharm’s marketing department. He has extensive experience in the exploration of biomarkers for cell identification and diagnostic purposes. His Ph.D. is in Cellular and Genetic Medicine from the University of Copenhagen. His academic background is in human embryonic stem cells and identification of cell of origin for the various types of breast cancer.