This paper focuses on the denoising and enhancing of 3-D reflection seismic data. We
propose a pre-processing step based on a non-linear diffusion filtering leading to a better …

This paper presents a novel technique for detection of point landmarks in volumetric medical
images based on a three-dimensional (3D) Phase Congruency (PC) model. A bank of 3D …

In this paper, we present a method for the decomposition of a volumetric image into its most
relevant visual patterns, which we define as features associated to local energy maxima of …

This work tackles the segmentation of apparent-motion from a bottom-up perspective. When
no information is available to build prior high-level models, the only alternative are bottom …

This paper focuses on the denoising and enhancing of 3D data. Our aim is to denoise the
3D blocks without blurring relevant details such as edges. In order to achieve this task, we …

Most existing object segmentation algorithms suffer from a so-called under-segmentation
problem, where parts of the segmented object are missing and holes often occur inside the …

In this paper, we present a method for the decomposition of a volumetric image into its most
relevant visual patterns, which we define as features associated to local energy maxima of …

The long-term goal of this research is the characterization of atherosclerosis lesions in vivo
using Magnetic Resonance Imaging (MRI). Our particular interest is the computer-aided …

Motion estimation by means of spatio-temporal energy filters–velocity tuned filters–is known
to be robust to noise and aliasing and to allow an easy treatment of the aperture problem. In …

This chapter deals with the problem of segmentation of apparent-motion. Apparent-motion
segmentation can be stated as the identification and classification of regions undergoing the …