Synopsis
Computer-Aided Oral and Maxillofacial Surgery: Developments, Applications, and Future Perspectives is an ideal resource for biomedical engineers and computer scientists, clinicians and clinical researchers looking for an understanding on the latest technologies applied to oral and maxillofacial surgery. In facial surgery, computer-aided decisions supplement all kind of treatment stages, from a diagnosis to follow-up examinations. This book gives an in-depth overview of state-of-the-art technologies, such as deep learning, augmented reality, virtual reality and intraoperative navigation, as applied to oral and maxillofacial surgery. It covers applications of facial surgery that are at the interface between medicine and computer science.
Examples include the automatic segmentation and registration of anatomical and pathological structures, like tumors in the facial area, intraoperative navigation in facial surgery and its recent developments and challenges for treatments like zygomatic implant placement.
- Provides comprehensive, state-of-the-art knowledge of interdisciplinary applications in facial surgery
- Presents recent algorithmic developments like Deep Learning, along with recent devices in augmented reality and virtual reality
- Includes clinical knowledge of two facials surgeons who give insights into the current clinical practice and challenges of facial surgeons in university hospitals in Austria and China
About the Authors
Jan Egger has over 10 years of experience in developing algorithms in medical image analysis and computer vision, including 5 years of postdoctoral research and development in the healthcare industry. He has extensive experience in implementing algorithms and software in the field of surgical planning, and published over 100 peer-reviewed papers and several patents. Jan holds a Ph.D. and a German Habilitation in Computer Science, and an interdisciplinary Ph.D. in Human Biology. The interdisciplinary Ph.D. was obtained when working in the Neurosurgery Department of the University Hospital in Marburg, Germany (Chairman Professor Dr. Nimsky), where he developed several algorithms for brain tumors, aneurysms and deep brain stimulation, which can be used within the Operation Microscope. He is the initiator of Studierfenster (studierfenster.at), an online platform for medical image analysis. His main research interests are Translational Science in Medical Image Analysis and Image-Guided Therapy. Jan has currently a dual appointment and is employed 50% at the Graz University of Technology and 50% at the Medical University of Graz.
Prof. Xiaojun Chen is with School of Mechanical Engineering, Shanghai Jiao Tong University (SJTU), China. He received his Ph. D from SJTU in 2006. His research focuses on computer assisted surgery, including biomedical image analysis, image-guided interventions, artificial intelligence in biomedical physics and analysis, VR/AR/MR technology in medicine, medical robotics and biomedical manufacturing. As a visiting professor, he had worked at Harvard Medical School, TIMC-IMAG lab (CNRS, France), the OMFS-IMPATH lab (KU Leuven, Belgium), and the CISTIB lab (the University of Sheffield, UK). He is the author and co-author of more than 200 peer-reviewed articles, and the PI of more than 30 research projects, including seven funded by National Natural Science Foundation of China. He was granted Second Prize of National Science & Technology Progress Award of China (2019). His important academic responsibilities include an associate editor of Computerized Medical Imaging and Graphics, and Computer Assisted Surgery, and a member of the editorial board of Physics in Medicine & Biology, International Journal of Computer Assisted Radiology and Surgery, and Medical Engineering & Physics.
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