Improved automated brachytherapy seed localization in trans-urethral ultrasound data

The utility of Trans-urethral ultrasound(TUUS) for permanent prostate brachytherapy is dependent on the quality of the data acquired. Previous work on Trans-urethral ultrasound suggested that TUUS acquires higher quality images than Trans-rectal ultrasound. Manual segmentation of TUUS data limits the utility of TUUS intra-operative, however, automated segmentation methods can be used to reduce the processing time. This research describes a segmentation paradigm which incorporates a priori information about the implanted seeds in order to provide a reasonable segmentation. The segmentation framework incorporates information about the size, shape, and orientation of the seeds. The paradigm integrates this information using fuzzy inference rules. The results show that the automated method is at least 4 times faster than manual segmentation. The sensitivity and specificity of the method were 76% and 93%, respectively. The decrease sensitivity is acceptable because it is the specificity which is more critical in determining if adequate dose has been delivered. Future work with this method will increase accuracy by incorporating additional information about the seeds.