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Clinical Image Quality Assessment (CLUES):


Bridging the gap between physical measurements 

and clinical performance in medical imaging

(April 2015-June 2019)

• Medical diagnostic imaging is one of the cornerstones of modern healthcare.

• The quality of the obtained images should enable the radiologists to accurately perform their diagnosis detecting or excluding the presence of abnormalities.

• Tecnhological advances appear continuosly. Their fast paced incorporation in healthcare makes it crucial to have objective and robust methods to assess the quality of the imaging systems.

• However, the current objective methods for quantifying image quality fall short to assess it in conditions close to the real clinical patient images. 

• There is a need for methods and techniques to assess clinical image quality. They are essential in deciding whether advanced technologies in radiology are suitable and well optimized for the intended clinical task or not. 

• The challenge of the CLUES project is to develop a framework that predicts the performance of radiologists in combination with imaging technology, for specific clinical detection tasks.

• This is an innovative concept based on new phantoms as a model for the patient and computer simulated observers (model observers) as a model for the radiologist. This results in a rapid, efficient and objective framework to assess clinical image quality.

Goal of CLUES: Efficient and objective evaluation of image quality related 

to a clinical task.