MICO - COgnitive virtual MIcroscopy

Towards smart scanners for breast cancer grading

Principal Investigators

Academic, Industrial and Medical Partners




A project supported by the French National Research Agency ANR, program TecSan 2010.
Reference ANR-10-TECS-015


Within the last decade, histopathology became widely accepted as a powerful exam for diagnosis and prognosis in mainstream diseases such as breast cancer. Currently, analysis of medical images in histopathology largely remains the work of human experts. For pathologists, this consists of hundreds of slides examined daily. Such a tedious manual work is often inconsistent and subjective. 

The cognitive microscope (MICO) aims at radically modifying the medical practices by proposing a new cognitive medical imaging environment able to improve reliability of decision making in histopathology. Our goal is to realize a generic, open-ended, semantic digital histology platform including a cognitive dimension. MICO combines visual perception, context, cognition and experience to reinforce a visual diagnosis assistance following an approach centered on user behavior. A pervasive adaptation platform through learning mechanisms facilitating fast, incremental and continuous learning of explicit and implicit medical knowledge, MICO is able to adapt to the context at different levels, including specific domain knowledge, information about the patient, partial interpretation of the visual content and subjective feedback from the user.

Breast cancer grading is developed, tested and validated in the frame of project MICO in order to demonstrate the viability and relevance of the system. Being part of a long term process, initiated by the experience of long-run industrial and university partners, MICO is an open system, easily deployable into several specific medical domains such as histopathology, cytopathology and hematology. Besides computer-aided diagnosis, the platform opens the way to a wide range of applications requiring manipulation of medical knowledge such as telepathology, datamining, teaching and education assistance. 

Use case : BCG and HIE quality support

Use case : BCG and HIE quality support

Role of the partners

IPAL/UJF Whole slide image exploration and analysis, medical ontologies, semantic indexing, virtual microscopy.
TRIBVN Core component of MICO platform, virtual microscope for pathology and dissemination/valorisation support.
LIP6/UPMC Context modelling and management.  GPU implementation.
GHU-PS Domain knowledge provider, medical validation, valorisation/dissemination support.
AGFA Healthcare Ontology engineering, formal knowledge modelling, modelling under uncertainty, data collection and aggregation (interoperability platform), knowledge authoring and repository, valorisation/dissemination support.
THALES-TCF Semantic middleware and valorisation/dissemination support.

Our International Benchmarking is UP:

Mitosis Detection in Breast Cancer Histological Images
ICPR 2012 International benchmark contest, November 11-15, 2012, Tsukuba, Japan