Fully automatic estimation of object pose for segmentation initialization: application to cardiac MR and echocardiography images
Meng Ma, Johan G. Bosch, Johan H. C. Reiber, Boudewijn P. F. Lelieveldt · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2007
Automatic image segmentation techniques are essential for medical image interpretation and analysis. Though numerous methods on image segmentation have been reported, the quality of a segmentation often heavily relies on the positioning of an accurate initial contour. In this paper, a novel solution is presented for the automated object detection in medical image data. A shape- and intensity template is generated from a training set, and both the search image and the template are mapped into a log-polar domain, where rotation and scale are represented by a translation. Orientation and scale of the object are estimated by determining maximum normalized correlation using a Symmetric Phase Only Matched Filter (SPOMF) with a peak enhancement filter. The detected orientation and scale are subsequently applied to the template, and a second pass of the SPOMF using the transformed template yields the actual position of the object in the search image. Performance tests were carried out on two imaging modalities: a set of cardiac MRI images from 34 patients and 2D echocardiograms from 100 patients.