Though conventional coronary angiography (CCA) has been the standard of reference for diagnosing coronary artery disease in the past decades, computed tomography angiography (CTA) has rapidly emerged, and is nowadays widely used in clinical practice. Here, we introduce a standardized evaluation framework to reliably evaluate and compare the performance of the algorithms devised to detect and quantify the coronary artery stenoses, and to segment the coronary artery lumen in CTA data. The objective of this evaluation framework is to demonstrate the feasibility of dedicated algorithms to: (1) (semi-)automatically detect and quantify stenosis on CTA, in comparison with quantitative coronary angiography (QCA) and CTA consensus reading, and (2) (semi-)automatically segment the coronary lumen on CTA, in comparison with expert's manual annotation. A database consisting of 48 multicenter multivendor cardiac CTA datasets with corresponding reference standards are described and made available. The algorithms from 11 research groups were quantitatively evaluated and compared. The results show that (1) some of the current stenosis detection/quantification algorithms may be used for triage or as a second-reader in clinical practice, and that (2) automatic lumen segmentation is possible with a precision similar to that obtained by experts. The framework is open for new submissions through the website, at http://coronary.bigr.nl/stenoses/.

International audienceThis article provides a brief overview of the quantum chemical auxiliary density functional theory program deMon2k. A basic introduction into its key computational features is given. By selected examples, it is shown how deMon2k can contribute to the elucidation of problems in chemistry, biology, and materials science such as finite temperature effects, nuclear magnetic resonance studies, structure determinations, heterogeneous, and enzymatic catalysi

Abstract. This paper proposes an automatic segmentation method of vessel walls that combines an implicit 3D model of the vessels and a total curvature penalizer in a level set evolution scheme. First, the lumen is segmented by alternating a model-guided level set evolution and a recalculation of the model itself. Second, the level set of the lumen is evolved with a term that aims at penalizing the total curvature and with a prior that forces the outer layer of the vessel towards the outside of the lumen. The model term is deactivated during this step. Finally, in a third step, the model term is reactivated in order to impose a smooth change of the radius along the vessel. Once the two segmentations have been computed, stenoses are detected and quantified at the thickest locations of the segmented vessel wall. Preliminary results show that the proposed method compares favorably with respect to the state-of-the-art both for synthetic and real CTA datasets.

Cartilage is primarily responsible for maintaining the stability of the large airways; yet very little is known about the mechanical properties of airway cartilage. This work establishes a technique whereby average values for the equilibrium modulus of excised tracheal cartilage rings can be obtained. An apparatus was designed to apply preset deformations to a tracheal segment and to monitor the deforming force. Segments of four human tracheae obtained postmortem and containing three rings were mounted in the apparatus after being stripped of posterior membrane. The load-deformation behavior was analyzed with a model on the basis of thin curved beam theory. Agreement between predicted deformed shapes and those observed was good in three of the four cases and in the case of a short length of longitudinally split rubber tube. The technique is suitable for comparing mechanical properties of cartilage before and after an intervention.

Abstract-This paper proposes two alternative formulations to reduce the high computational complexity of tensor voting, a robust perceptual grouping technique used to extract salient information from noisy data. The first scheme consists of numerical approximations of the votes, which have been derived from an in-depth analysis of the plate and ball voting processes. The second scheme simplifies the formulation while keeping the same perceptual meaning of the original tensor voting: the stick tensor voting and the stick component of the plate tensor voting must reinforce surfaceness, the plate components of both the plate and ball tensor voting must boost curveness, whereas junctionness must be strengthened by the ball component of the ball tensor voting. Two new parameters have been proposed for the second formulation in order to control the potentially conflictive influence of the stick component of the plate vote and the ball component of the ball vote. Results show that the proposed formulations can be used in applications where efficiency is an issue, since they have a complexity of order O 1 . Moreover, the second proposed formulation has been shown to be more appropriate than the original tensor voting for estimating saliencies by appropriately setting the two new parameters.