Description
Date depot: 29 mars 2018
Titre: Intelligent Exploration of Whole Slide Image for Digital Pathology
Directeur de thèse:
Nicolas LOMENIE (LIPADE)
Directeur de thèse:
Julien CALDERARO (APHP (UP))
Encadrant :
Christophe KLEIN (CRC)
Domaine scientifique: Sciences et technologies de l'information et de la communication
Thématique CNRS : Intelligence artificielle
Resumé:
Project
Digital Histopathology is on the verge of a revolution and we
need to consolidate the trend at the National/Regional level. We have
already built upon a local community few lines of research. In
particular, a recent collaboration about assessment of lymphocyte
infiltration out of Whole Slide Image for clinical applications has led
to publication and on)going patent proposal with SATT Innov IdF.
We would like to go further in that direction by proposing a
fully-fledged processing pipeline (big data and image processing)
including machine learning modules (deep learning) to tackle a wide
range of biological issues about analysis of digital tissue landscapes
(from clinical diagnosis to tumor environment analysis).
Challenges
The scientific challenges are manyfold :
color analysis
topological analysis
data
analyses pipelines
fully integrated in a so-called 'post-genomic microscope' in which
relations between genetic analysis can be correlated to high precision
phenotypic description.
International challenge
The challenge is clearly international and most advanced countries are running for proposing solutions.
Doctorant.e: Zeng Qinghe