Three-dimensional reconstruction of myocardial contrast perfusion from biplane cineangiograms by means of linear programming techniques

The assessment of coronary flow reserve from the instantaneous distribution of the contrast agent within the coronary vessels and myocardial muscle at the control state and at maximal flow has been limited by the superimposition of myocardial regions of interest in the two-dimensional images. To overcome these limitations, we are in the process of developing a three-dimensional (3D) reconstruction technique to compute the contrast distribution in cross sections of the myocardial muscle from two orthogonal cineangiograms. To limit the number of feasible solutions in the 3D-reconstruction space, the 3D-geometry of the endo- and epicardial boundaries of the myocardium must be determined. For the geometric reconstruction of the epicardium, the centerlines of the left coronary arterial tree are manually or automatically traced in the biplane views. Next, the bifurcations are detected automatically and matched in these two views, allowing a 3D-representation of the coronary tree. Finally, the circumference of the left ventricular myocardium in a selected cross section can be computed from the intersection points of this cross section with the 3D coronary tree using B-splines. For the geometric reconstruction of the left ventricular cavity, we envision to apply the elliptical approximation technique using the LV boundaries defined in the two orthogonal views, or by applying more complex 3D-reconstruction techniques including densitometry. The actual 3D-reconstruction of the contrast distribution in the myocardium is based on a linear programming technique (Transportation model) using cost coefficient matrices. Such a cost coefficient matrix must contain a maximum amount of a priori information, provided by a computer generated model and updated with actual data from the angiographic views. We have only begun to solve this complex problem. However, based on our first experimental results we expect that the linear programming approach with advanced cost coefficient matrices and computed model will lead to a

Fuzzy-Rule Generation Using Incremental Learning for a Knowledge-Based Anaesthesia Monitor

This paper discusses an incremental learning algorithm: Fuzzy Incremental Learning. The algorithm was developed to obtain a rule-base for a knowledge-based signal analysis system to be used in anaesthesia. The algorithm has a domain-dependent part, which can be obtained by simplified expert interviews. Furthermore, it deals with uncertainty in the observations and it is capable of updating the knowledge base as soon as new events have been observed. 1 Introduction This section explains the motivation for the Fuzzy Incremental Learning algorithm. It discusses the need for a knowledge-based signal analysis system in anaesthesia monitoring and the problem of knowledge acquisition. 1.1 Anaesthesia Monitoring The Intelligent Anaesthesia Monitor project, in which the present study is embedded, aims at a knowledgebased signal analysis system that improves a patient's safety during surgery. Currently, the anaesthetist is overloaded by data from the equipment surrounding the patient in moder..

Knowledge-based segmentation for automatic Map interpretation

In this paper, a knowledge-based framework for the top-down interpretation and segmentation of maps is presented. The interpretation is based on a priori knowledge about map objects, their mutual spatial relationships and potential segmentation problems. To reduce computational costs, a global segmentation is used when possible, but an applicable top-down segmentation strategy is chosen when errors in the global segmentation are detected. The interpretation system has been tested on utility maps and the experiments show that when a top-down resegmentation strategy is used to correct errors in the global segmentation, the recognition performance is improved significantly. © Springer-Verlag Berlin Heidelberg 1996

Fundamentals of image processing

111 tr. ; 29 cm

Fundamentals of image processing

111 tr. ; 29 cm

Estimating Facial Expressions by Reasoning

This paper discusses our ideas about the automatic estimation of facial expressions. This research takes place within an intended project which has as objective: "The design and implementation of a non-invasive, audio-visually controlled facial synthesis system". Here, the (acted) facial expressions of a user have to be recognized on the basis of audio and video recordings, which can then be applied to a computer model of a human face, or even of an animation character, to create life-like animation films