P. Radeva, D. Rotger, E. Nofrerias, and J. Mauri (Spain)
coronary vessels, lesion detection, angiograms, IVUS, multimodal image fusion, deformable models
The growing appreciation of the pathophysiological and prognostic importance of arterial morphology has led to the realization that angiograms are inherently limited in defin ing the distribution and extension of coronary wall disease. By Intravascular Ultrasound images physicians have a pic ture of the composition of vessel in detail. However, ob serving an intravascular ultrasound stack of images, it is difficult to figure out the image position and extension with regard to the vessel parts and ramifications, and misclassi fication or misdiagnosis of lesions is possible. The objec tive of this work is to develop a computer vision technique to fuse the information from angiograms and intravascular ultrasound images defining the correspondence of every ul trasound image with a corresponding point of the vessel in the angiograms.
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