(Taken from application abstract): Digital images obtained from diagnostic medical procedures and archived in high-speed networks are an immense scientific resource. Our laboratory has developed database techniques for organizing image archives in such a way that images can be indexed and retrieved on the basis of pictorially defined image features. We have developed a geometric reasoning engine which indexes images on the basis of """"""""explicit"""""""" and """"""""implicit"""""""" geometric properties of anatomy. We have evaluated the performance of our methods on a collection of static cardiac MRI images. The technique automatically organizes such a collection into image view-plane (axial, sagittal, oblique, etc.) without prior definition, and can structure image collections on a notion of """"""""shape"""""""" that correlates well with that of expert radiologists. We propose to extend these concepts to index moving image sequences of the type found in diagnostic cardiology. We will investigate the use of quantitative parameters derived from the analysis of non-rigid motion as a means to index image sequence data. We believe that we can apply our laboratory's experience with shape and non-rigid motion analysis to moving image sequences so that they can be ordered and retrieved on the basis of similarity of shapemotion, a concept which is useful in such disciplines as cardiac diagnostic function assessment. Although our approach is applicable to a number of imaging modalities, we chose the area of echocardiographic imaging as our focus in order to capitalize on our expertise and the availability of data. We have a large collection of digital echocardiographic video sequences gathered on CD-ROMs for educational purposes and we will index these with the techniques we propose to develop.
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