New strategies for addressing the diversity-validity dilemma with big data.

The diversity-validity dilemma is one of the enduring challenges in personnel selection. Technological advances and new techniques for analyzing data within the fields of machine learning and industrial organizational psychology, however, are opening up innovative ways of addressing this dilemma. Given these rapid advances, we first present a framework unifying analytical methods commonly used in these two fields to reduce group differences.

Multi-layer deformation estimation for fluoroscopic imaging.

Accurate estimation of motion in fluoroscopic imaging sequences is critical for improved frame interpolation/extrapolation, tracking of surgical instruments, and Digital Subtraction Angiography (DSA). The projection of multiple transparent objects undergoing multiple complicated deformations in 3D onto a single 2D view makes this motion estimation problem quite challenging and ill-suited to existing techniques used in medical image analysis. We propose a novel method for jointly decomposing the observed image into a set of additive layers each associated with its corresponding smooth nonlinear deformation, which together model the non-smooth motion observed in the projection images across several frames.