Model observers play an important role in the optimization and assessment of imaging
devices. In this review paper, we first discuss the basic concepts of model observers, which …

This article will discuss very different ways of using machine learning that may be less
familiar, and we will demonstrate through examples the role of these concepts in medical …

With medical imaging technologies growth, the question of their assessment on the impact
and benefit on patient care is rising. Development and design of those medical imaging …

It is widely accepted that the optimization of medical imaging system performance should be
guided by task-based measures of image quality (IQ). Task-based measures of IQ quantify …

Magnetic resonance (MR) imaging offers a wide variety of imaging techniques. A large
amount of data is created per examination which needs to be checked for sufficient quality in …

The quality of an image affects its utility and image quality assessment has been a hot
research topic for many years. One widely used measure for image quality assessment is …

Many new reconstruction techniques have been deployed to allow low-dose CT
examinations. Such reconstruction techniques exhibit nonlinear properties, which …

The channelized Hotelling observer (CHO) has become a widely used approach for
evaluating medical image quality, acting as a surrogate for human observers in early-stage …

Purpose The purpose of this study was the evaluation of anthropomorphic model observers
trained with neural networks for the prediction of a human observer's performance. Methods …

Model observers (MO) are widely used in medical imaging to act as surrogates of human
observers in task-based image quality evaluation, frequently towards optimization of …