Inexact coronary tree matching algorithm with artificial nodes.

Coronary tree matching is applied to plan percutaneous vascular procedures. This work, which allows following each segment of non-isomorphic coronary trees over time, precedes the determination of the best 2D angiography view from C-arm acquisition system for angioplasty procedure. To match two 3D coronary trees which represent two successive cardiac phases, we adapted a reference inexact tree matching algorithm based on association graph and maximum clique.

Automatic kidney segmentation in CT images based on multi-atlas image registration.

Kidney segmentation is an important step for computer-aided diagnosis or treatment in urology. In this paper, we present an automatic method based on multi-atlas image registration for kidney segmentation. The method mainly relies on a two-step framework to obtain coarse-to-fine segmentation results.

Quantitative measurement of coronary artery stenosis in CCTA images using a 2D parametric intensity model.

In this paper, we propose an approach based on 2D vessel model to segment the vessel lumen in three-dimensional coronary computed tomographic angiography (CCTA) images. The 2D parametric intensity model is introduced first to simulate the intensity distribution of vessel lumen with different size in the longitudinal images. Then the Levenberg-Marquardt method is applied to fit the model within a series of region-of interests defined in the longitudinal image.

2-D impulse noise suppression by recursive gaussian maximum likelihood estimation.

An effective approach termed Recursive Gaussian Maximum Likelihood Estimation (RGMLE) is developed in this paper to suppress 2-D impulse noise. And two algorithms termed RGMLE-C and RGMLE-CS are derived by using spatially-adaptive variances, which are respectively estimated based on certainty and joint certainty & similarity information. To give reliable implementation of RGMLE-C and RGMLE-CS algorithms, a novel recursion stopping strategy is proposed by evaluating the estimation error of uncorrupted pixels.

Coronary vein extraction in MSCT volumes using minimum cost path and geometrical moments.

This work deals with the extraction of patient-specific coronary venous anatomy in preoperative multislice computed tomography (MSCT) volumes. A hybrid approach has been specifically designed for low-contrast vascular structure detection. It makes use of a minimum cost path technique with a Fast-Marching front propagation to extract the vessel centerline.