Conclusion

Abstract

This monograph introduces a set of algorithms that computationally plan and optimize image-guided medical procedures based on imaging data and physician-specified clinical criteria. These computational methods bridge the gap between medical imaging, where emerging advancements are enabling clinicians to non-invasively examine anatomy and metabolic processes in detail, and medical robotics, which is rapidly gaining acceptance in clinical practice.

The monograph focuses on three motion planning problems that arise in image-guided medical procedures: motion planning for rigid needles, motion planning for steerable needles , and motion planning for radiation sources for cancer treatment. Each of these motion planning problems introduces new computational challenges and is subject to unique planning and optimization constraints imposed by the physician’s treatment requirements, the patient’s anatomy, and the physical limitations of medical equipment and devices. We present planning and optimization algorithms for each of these general problems, and then customize the solutions to the specific application of prostate brachytherapy.