Artificial intelligence for the evaluation of profiles, trajectories and management of vulnerability in health: COVID-19, frailty of the elderly and cancer
Matricis.ai
Detection of endometriosis lesions from MRI images
Underway
01/09/2022
-
30/09/2023
Main objectives
Develop AI software to detect and characterize endometriosis on pelvic MRI
Challenge
Endometriosis is a disease that is still poorly known and poorly diagnosed. The average length of time before a patient is diagnosed is 7 years after the onset of the first symptoms and 75% of patients receive at least one erroneous diagnosis. Diagnostic errors are partly due to the difficulty of analyzing pelvic MRI images and the lack of specialized radiologists, who represent less than 1% of radiologists in France and are poorly distributed throughout the country.
Methodology/Technology used
The project employs a set of machine learning technologies to recognize and model the organs of the female pelvis and classify the different types of endometriosis lesions according to their location.
Contacts
Elise Mekkaoui () & Raphaelle Taub ()
Members
AP-HP, Inria
Useful links
https://matricis.ai/
Other projects
Description
Learning a deep representation of patient records for event prediction and patient segmentation
Names of partners involved
AP-HP, Inria