Brigham and Women's Hospital and Harvard Medical School
Most tissues in the human body are not transparent. This is one of the fundamental limitations of conventional surgery. The objective of image guided therapy (IGT) is to overcome this limitation through the use of volumetric diagnostic imaging. All imaging modalities available in a modern radiology department have been used for IGT procedures. In its most advanced implementation, IGT requires "on-line" processing of intraoperatively acquired image data. Preoperative images need to be modified to incorporate intraoperative changes.
The computer science component of IGT is addressed with algorithms from the fields of applied mathematics, computer vision, computer graphics, and systems engineering. For working solutions, segmentation, registration and sophisticated rendering techniques have to be combined into complex software systems. It takes years to develop the appropriate algorithmic approaches and to implement them into practical systems. High performance computing (HPC) can be used in IGT as a "time machine", giving scientists and engineers access to future levels of computational performance today. This requires the integration of proper parallelization and network communication technologies.
The presentation will introduce the application domain and algorithms and will give examples for the successful execution of IGT concepts in real surgical and interventional procedures using magnetic resonance imaging.