We present an automated algorithm for tissue segmentation of noisy, low contrast magnetic resonance (MR) images of the brain. We use a mixture model composed of a large number of G...
Combination of multiple segmentations has recently been introduced as an effective method to obtain segmentations that are more accurate than any of the individual input segmentati...
Vibro-elastography is a new medical imaging method that identifies the mechanical properties of tissue by measuring tissue motion in response to a multi-frequency external vibratio...
Current methods of four-dimensional (4D) CT imaging of the thorax synchronise the acquisition with a respiratory signal to restrospectively sort acquired data. The quality of the 4...
The growing usage of statistical shape analysis in medical imaging calls for effective methods for highly accurate shape correspondence. This paper presents a novel landmark-based ...
In Emission Tomography imaging, respiratory motion causes artifacts in lungs and cardiac reconstructed images, which lead to misinterpretations and imprecise diagnosis. Solutions l...
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...