Fast retrieval using organ shapes is crucial in medical image databases since shape is a clinically prominent feature. In this paper, we propose that 2-D shapes in medical image da...
We propose a novel method for quantitative interpretation of uncalibrated optical images which is derived explicitly from an analysis of the image formation model. Parameters chara...
Stephen J. Preece, I. B. Styles, S. D. Cotton, Ela...
Validation and method of comparison for segmentation of magnetic resonance images (MRI) presenting pathology is a challenging task due to the lack of reliable ground truth. We prop...
We present a statistical framework that combines the registration of an atlas with the segmentation of magnetic resonance images. We use an Expectation Maximization-based algorithm...
Kilian M. Pohl, John W. Fisher III, James J. Levit...
Abstract. This paper describes a new framework for white matter tractography in high angular resolution diffusion data. A direction-dependent local cost is defined based on the dif...
Eric Pichon, Carl-Fredrik Westin, Allen Tannenbaum
Abstract. In this paper we present a novel method for building a 4D statistical atlas describing the cardiac anatomy and how the cardiac anatomy changes during the cardiac cycle. T...
Dimitrios Perperidis, Raad Mohiaddin, Daniel Rueck...
In inter-subject registration, one often lacks a good model of the transformation variability to choose the optimal regularization. Some works attempt to model the variability in a...
Xavier Pennec, Radu Stefanescu, Vincent Arsigny, P...
Vulnerable plaques are dangerous atherosclerotic lesions that bear a high risk of complications that can lead to heart attacks and strokes. These plaques are known to be chronicall...
Sean M. O'Malley, Manolis Vavuranakis, Morteza Nag...
We present a novel method for finding white matter fiber correspondences and clusters across a population of brains. Our input is a collection of paths from tractography in every b...
Shape priors attempt to represent biological variations within a population. When variations are global, Principal Component Analysis (PCA) can be used to learn major modes of vari...
Delphine Nain, Steven Haker, Aaron F. Bobick, Alle...