Generation of synthetic images of chest radiography with chronic obstructive pulmonary disease using artificial intelligence techniques

The main purpose of this research is to propose a strategy to generate synthetic chest x-ray images from data of clinical interest. The generated images should visually reproduce lung disease based on the selected input characteristics. This requires the processing and analysis of images using algorithms that identify the most relevant characteristics and variables to represent the lung disease, in contrasted with the information available in clinical practice.
Thereafter, a computational model will be implemented and assessed to generate synthetic images using artificial intelligence techniques. The results of this research can be applied to the generation of tools which facilitate the processes of clinical training and research, for the interpretation of physiological and pathological phenomena.

Faculty Supervisor:

Luc Duong

Student:

Partner:

Universidad EIA

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology; Education

University:

École de technologie supérieure

Program: