  Radiological imaging of prostate is becoming more popular among researchers
and clinicians in searching for diseases, primarily cancer. Scans might be
acquired at different times, with patient movement between scans, or with
different equipment, resulting in multiple datasets that need to be registered.
For this issue, we introduce a registration method using anatomical
feature-guided mutual information. Prostate scans of the same patient taken in
three different orientations are first aligned for the accurate detection of
anatomical features in 3D. Then, our pipeline allows for multiple modalities
registration through the use of anatomical features, such as the interior
urethra of prostate and gland utricle, in a bijective way. The novelty of this
approach is the application of anatomical features as the pre-specified
corresponding landmarks for prostate registration. We evaluate the registration
results through both artificial and clinical datasets. Registration accuracy is
evaluated by performing statistical analysis of local intensity differences or
spatial differences of anatomical landmarks between various MR datasets.
Evaluation results demonstrate that our method statistics-significantly
improves the quality of registration. Although this strategy is tested for
MRI-guided brachytherapy, the preliminary results from these experiments
suggest that it can be also applied to other settings such as transrectal
ultrasound-guided or CT-guided therapy, where the integration of preoperative
MRI may have a significant impact upon treatment planning and guidance.

Computer Vision and Pattern Recognition;Graphics