Ph.D. candidate Ph.D. candidate Faculté des sciences et de génie Université Laval

The aim of this doctoral thesis is to develop a tool able to automatically provide organs of interest segmentations on computed tomography images using machine learning techniques.

This tool will then be used to calculate organ doses in order to establish personalized dosimetric records in medical imaging. Doses will be calculated using informations obtained from images, radiographic technique and GPU-based Monte Carlo dose calculation algorithm (GPUMCD). Automated pipelines will be implemented to process large amounts of data.

This project permits to better evaluate the exposure of the population to ionizing radiation caused by medical imaging procedures

Personalized dosimetry in computed tomography imaging

Discover

Featured project

Intraoperative analgesic treatment decisions based on the NOL index: contribution of a data-based approach to improve accuracy and relevance

Student member : Marzieh Ghiyasinasab

This research project is based on the analysis of massive data on the NOL index and other intraoperative clinical parameters used by anesthesiologists during surgery. These parameters help them make analgesic treatment decisions in a non-communicating patient under general anesthesia and in whom it is impossible to assess pain and analgesic needs by standard questionnaires performed on awake patients. 
First, the objective is to interpret the values of this index in relation to the decisions made by the clinician. 

Read more