Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
On active contour models and balloons
CVGIP: Image Understanding
Digital image processing
Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
STACOM'12 Proceedings of the third international conference on Statistical Atlases and Computational Models of the Heart: imaging and modelling challenges
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Tomoscintigraphy (3-D data representing the myocardium perfusion) and coronarography (X-ray image sequences acquired from several viewpoints and providing information about the coronary artery tree state) are widespread examinations used standardly for the diagnosis of cardiovascular diseases. Currently, the data of both examinations are separately analyzed by the specialists who are often not able to visually link the information of the two modalities. The aim of this work is to facilitate the diagnosis by providing the specialist with 3-D representations highlighting the relationship between stenoses (artery narrowing, disease cause) and perfusion defaults (muscle necrosis, consequence). In such representations, the structure of a schematic artery tree and the stenosis positions are 3-D reconstructed and set onto the perfusion volume. The reconstruction algorithm starts with the projection of the perfusion volume on planes parallel to the X-ray images. In this way, 2-D tomographic images are generated for each viewpoint of the coronarography. The borders of the myocardium shadow visible in the X-ray images are then segmented with an active contour method. These contours are registered with their homologuous structures from the corresponding 2-D tomographic images. The geometrical transformations obtained for each coronarographic viewpoint are used to place artery points marked by cardiologists in the X-ray images (stenoses, artery beginnings, ends and bifurcations) in their corresponding positions in the tomographic images. Finally, the schematic artery tree is set on the perfusion volume using the homologous points of the different viewpoints and a parallel projection model. The main advantage of this method is that the clinical acquisition protocols remain unchanged, no calibration of the acquisition systems being needed. Results are given for a phantom and a database of patients in order to validate the proposed method.