Qualimetrics

Broad Goals

1. Assessing quality in the presence of texture
2. Devising quality metrics beyond noise limited ones
3. Metrology in the context of mathematical observer models and/or human perception.

Medical imaging technologies are a cornerstone of modern healthcare and are pivotal to deliver on the promise of “precision medicine.” However, the diversity, complexity, and potential risks associated with imaging examinations make it challenging to optimize the use of such technologies. The objective of qualimetrics research is to devise and apply patient relevant metrics related to the quality of medical imaging examinations, with a particular focus on measuring image quality. Specific areas of interest are assessing image quality in the presence of anatomical texture, devising quality metrics for imaging tasks that are not solely noise limited, and the application of mathematical observer models and human perception science. Current projects are focused on how image quality affects detection and estimation tasks in standard, cardiac, and dual energy computed tomography imaging.

Related Publications

1. Effect of radiation dose reduction and reconstruction algorithm on image noise, contrast, resolution, and detectability of subtle hypoattenuating liver lesions at multidetector CT: filtered back projection versus a commercial model–based iterative reconstruction algorithm.
2. Quantitative comparison of noise texture across CT scanners from different manufacturers.
3. Comparison of low‐contrast detectability between two CT reconstruction algorithms using voxel‐based 3D printed textured phantoms.