Teaching Medical Students Optimal Consulting Skills: The Challenge of Generating Better Referring Physicians.

Rationale and objectives We sought to incorporate a new teaching module into the traditional medical student radiology clerkship, to improve the necessary skills for future referring physicians. Materials and methods A new required and graded module was introduced in 2014 into the radiology clerkship in year three of medical school: the Mystery Case. Each student was provided a unique and undifferentiated case from a dedicated teaching file containing de-identified images and requisition data.

Computerized assessment of motion-contaminated calcified plaques in cardiac multidetector CT.

An automated method for evaluating the image quality of calcified plaques with respect to motion artifacts in noncontrast-enhanced cardiac computed tomography (CT) images is introduced. This method involves using linear regression (LR) and artificial neural network (ANN) regression models for predicting two patient-specific, region-of-interest-specific, reconstruction-specific and temporal phase-specific image quality indices. The first is a plaque motion index, which is derived from the actual trajectory of the calcified plaque and is represented on a continuous scale.