Estimating Continuous 4D Wall Motion of Cerebral Aneurysms from 3D Rotational Angiography

This paper presents a technique to recover dynamic 3D vascular morphology from a single 3D rotational X-ray angiography acquisition. The dynamic morphology corresponding to a canonical cardiac cycle is represented via a 4D B-spline based spatiotemporal deformation. Such deformation is estimated by simultaneously matching the forward projections of a sequence of the temporally deformed 3D reference volume to the entire 2D measured projection sequence. A joint use of two acceleration strategies is also proposed: semi-precomputation of forward projections and registration metric computation based on a narrow-band region-of-interest. Digital and physical phantoms of pulsating cerebral aneurysms have been used for evaluation. Accurate estimation has been obtained in recovering sub-voxel pulsation, even from images with substantial intensity inhomogeneity. Results also demonstrate that the acceleration strategies can reduce memory consumption and computational time without degrading the performance.</p

A neurodynamical model of brightness induction in V1

Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. Recent neurophysiological evidence suggests that brightness information might be explicitly represented in V1, in contrast to the more common assumption that the striate cortex is an area mostly responsive to sensory information. Here we investigate possible neural mechanisms that offer a plausible explanation for such phenomenon. To this end, a neurodynamical model which is based on neurophysiological evidence and focuses on the part of V1 responsible for contextual influences is presented. The proposed computational model successfully accounts for well known psychophysical effects for static contexts and also for brightness induction in dynamic contexts defined by modulating the luminance of surrounding areas. This work suggests that intra-cortical interactions in V1 could, at least partially, explain brightness induction effects and reveals how a common general architecture may account for several different fundamental processes, such as visual saliency and brightness induction, which emerge early in the visual processing pathway.Publisher PDFPeer reviewe