Paper
29 April 2005 Seed image reconstruction using a template matching technique
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Abstract
One of the problems in fluoroscopy based 3D seed reconstruction for prostate brachytherapy is the clustering of seeds in the fluoroscopic images. A template matching based method is proposed in this study to reconstruct the orientations and locations of individual seed images in the cluster. An idealized projection image of implanted seeds was used as a template to reconstruct the cluster, and different optimization strategies were implemented to find the best orientation and location for individual seeds. The four search methods compared were: 1) Down hill simplex method; 2) Powell method; 3) Multi-resolution based method with exhaustive initial search; and 4) Multi-resolution based method without exhaustive initial search. These methods were applied to 10 test images. Five of the ten images had only 2-seed clusters and five had 3-seed clusters. The results demonstrate that the first two methods didn’t perform well, and that the results were dependent on the initial guesses used to start the optimization process. The third method successfully found the best configurations for all of the 10 images while the fourth method succeeded in 9 of the 10 cases. We conclude therefore that multi-resolution approaches are appropriate for the seed image reconstruction problem. Since the possible configurations of the template are pre-computed, an additional advantage is that less execution time was needed for the multi-resolution methods. When applied to the seed image reconstruction process, this method will potentially significantly improve the accuracy of the 3D reconstruction of implanted seeds from fluoroscopic images used in prostate brachytherapy.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yi Su and Richard A. Robb "Seed image reconstruction using a template matching technique", Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); https://doi.org/10.1117/12.594396
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Cited by 7 scholarly publications.
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KEYWORDS
Image restoration

Image processing

Prostate

3D image reconstruction

3D image processing

Fluoroscopy

Binary data

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