LAZARD Tristan

PhD student

Mines ParisTech

tristan.lazard [at]

Short bio

Master 2 Mathematics and applications, UPMC

Thesis title

Deep learning for digital pathology: from full to no supervision.

Short abstract

Digital pathology involves studying digital versions of tissue slides to make diagnoses or derive prognostic markers from cells and tissue features. Deep learning can automate some diagnostic steps or help discover associations between phenotype and genotype.  However, these slides are large, with full magnification versions weighing up to 16GB uncompressed, which therefore raises specific challenges. The goal of this PhD is to determine the best supervision methods to extract information from these slides.