Biomedical imaging systems are developed primarily for diagnostic or scientific measurement rather than for guiding tools and actuators. Imaging systems suitable for guidance pose unique requirements, including real-time operation, registration between multiple 3D coordinate frames, and device geometries that allow physical access for manipulations and ancillary equipment. Real-time computer vision algorithms to detect and track targets may be desired, and guidance of human operators additionally requires well-designed visualization and augmented reality interfaces. Analysis and design of such biomedical image guidance systems will be described, including software, hardware, computer-controlled optics, and human factors research. This novel work applies and extends recently developed optical and acoustical modalities, including a microsurgical augmented reality system and a unique multi-modal approach to enhancing medical ultrasound of the patient's interior anatomy with simultaneous computer vision of the patient's exterior.
John Galeotti received BS and MS degrees in Computer Engineering from North Carolina State University (2001, 2002), and MS and PhD degrees in Robotics from Carnegie Mellon University (2005, 2007). He is currently a senior project scientist at Carnegie Mellon University’s Robotics Institute, as well as an adjunct assistant professor with advising privileges at both CMU's Biomedical Engineering department and at the University of Pittsburgh's Bioengineering department. He directs the Biomedical Image Guidance Laboratory at CMU, and he teaches a graduate course on biomedical image analysis algorithms that was funded by the National Library of Medicine.
Faculty Host: George Stetten
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