Modeling and Simulation for Medical Applications
||Celina Z. Imielinska, Ph.D.|| Dimitris Metaxas. Ph.D.|
|Associate Research Scientist||Professor of Computer Science and Biomedical Engineering|
|Columbia University||Rutgers the State University of New Jersey|
|College of Physicians and Surgeons|
|Dept. of Biomedical Informatics and||Dept. of Computer Science|
|701 168th Str. HSCC 201||110 Frelinghuysen Road|
|New York, NY||Piscataway, NJ 08854-8019|
|Tel: (212) 305 1440||Tel: (732) 445-0636|
|FAX: (212) 304 8388||FAX: (732) 445-0537|
Developing new methodologies for modeling and simulation is the central challenge behind building computer-based training tools for medicine (e.g. training for basic skills in anesthesiology/surgery, and minimally invasive surgical procedures). Major medical centers are interested in forming programs to teach, train, certify and re-certify medical practitioners using new simulation technologies. This course presents modeling and simulation techniques along with their graphical output for medical applications. It covers the medical data acquisition, segmentation, organ modeling, rendering and visualization, registration, virtual surgery and simulation, augmented reality, and a variety of clinical and educational applications.
Celina Z. Imielinska, Ph.D.
Associate Research Scientist
Dimitris Metaxas, Ph.D.
Professor of Computer Science and Biomedical Engineering
Rutgers the State University of New Jersey
B. Proposed Length
Half a Day
C. Summary Statement
Developing computer-based training tools for minimally invasive medical procedures (e.g. training for basic skills in anesthesiology/surgery, and minimally invasive surgical procedures) requires new methodologies for modeling and simulation. Major medical centers are interested in forming programs to teach, train, certify and re-certify medical practitioners using new simulation technologies. This course presents modeling and simulation techniques along with their graphical output for medical applications. It covers the medical data acquisition, segmentation, organ modeling, rendering and visualization, registration, virtual surgery and simulation, augmented reality, and a variety of clinical and educational applications.
D. Expanded Statement
This course is intended to demonstrate the state-of-the-art in interactive and real-time modeling techniques, spanning a number of educational and clinical medical applications, where the use of graphical representations of organ anatomy and physiology is necessary. Applications include methods for the acquisition and representation of medical data, organ visualization and segmentation methods, surface-based reconstruction and digital surfaces, "intuitive manipulation" and "alternate viewing" of large volumetric models, data driven implicit models, virtual patient from Visible Human data, virtual anatomy atlases, augmented patient simulators, modeling the shape and motion of the heart (combined left and right ventricle heart model), breast modeling for minimally invasive procedure, real-time tracking and visualization of knee joint motion, and physiological model of real-time breathing lungs.
All the speakers have the necessary experience to present this course at the right mathematical and medical level for our audience.
Basic knowledge of calculus, linear algebra, physics, and graphics. No required knowledge of medicine, as it will be given by the presenters. Special effort will be taken to present the mathematics and physics involved in an intuitive and easy to understand fashion. A casual interest in the topic will suffice.
G. Course Speakers
Celina Imielinska, Ph.D.
Deborah Silver, Ph.D.
Terry Yoo, Ph.D.
Dimitris Metaxas, Ph.D.
Jannick Rolland, Ph.D.
H. Course Syllabus
9am Welcome and Overview (Metaxas)
9:15 The Virtual Patient from the Visible Human Data (Imielińska)
- Issues with human diversity
- Overview of data visualization methods
- Visualization of large color datasets
- Visible Human Male foot anatomy lesson
- the role of 3D visualization of anatomy in simulators for minimally
9:45 Large Volumetric data Manipulation (Silver)
10:15 Deformable Implicit Surfaces (Yoo)
10:45 Modeling for the Integrated Recovery of Structure and Function from
Medical Images (Metaxas)
- Deformable models and Random Markov Fields
11:15 Augmented Reality: Aims and Challenges (Rolland)
11:45am: The Future of Modeling and Simulation Methods in Medicine (All Speakers)
I. Course Notes
A special emphasis will be placed on providing course notes that present the methodologies and applications in a clear and intuitive way. The presentation of the course will allow people with a general knowledge of graphics and interest in this area to be able to attend the course and comprehend the notes. We will also provide web pointers to relevant additional information and animations based on the presenter's work or related work by others.
A major goal of this course will be to stir increased interest in the graphics community to this exciting area of applications where graphics methods are of paramount importance.
J. Course Format
The format will be classroom style with lectures and considerable video material and live presentations. A panel discussion by all speakers at the end will address future directions of modeling methods in medical applications, and allow questions from the attendees.
K. Presentation Media
For the presentations we will be using PC-laptops, computers and videotapes.
L. Speaker Biosketches
Celina Imielinska, Ph.D.is an Associate Research Scientist at the Columbia University College of Physicians and Surgeons, Department of Medical Informatics, Office of Scholarly Resources, and the Department of Computer Science. She is one of the founders of the Vesalius Project where she took the lead on the technical problems of the medical image segmentation and 3D medical visualization. Dr. Celina Imielinska, has been trained as a computer scientist and electrical engineer. She holds B.E and M.E degrees in Electrical Engineering from Politechnika Gdanska, Poland, and M.S. and Ph.D. degrees in Computer Science from Rutgers University. Her current interests are in 3D visualization, computational geometry, image processing, and approximate algorithms for optimization problems. She has been supported by the NSF POWER grant on "Technical Challenges of 3D Visualization of Large Color Data Sets". She is the leader of the Columbia team on the NLM-funded contract on "Visible Human Project Registration and Segmentation Toolkit", where she is developing hybrid segmentation methods for medical images. In addition to conducting research and developing methodology for image processing and 3D modeling, she has been involved in developing the actual 3D visualizations of anatomy from the Visible Human dataset, which have been used in electronic anatomy curriculum at Columbia's medical school.
Deborah Silver, Ph.D., is an Associate Professor in the Dept. of Electrical and Computer Engineering at Rutgers, The State University of New Jersey. She received a B.S. from Columbia University School of Engineering in 1984 and an MS. (1986) and a Ph.D. (1988) from Princeton University in Computer Science. Her area of research is Scientific Visualization and Computer Graphics and she is the PI of the Vizlab, which is part of the CAIP Center at Rutgers University. She has taught courses in Computer Graphics, Visualization, Data Structures, Software Engineering and Robotics. She has worked on many aspects of visualization and is currently involved in distributed visualization, volume graphics, oceanographic visualization, and multimedia research efforts. She has
Dimitris Metaxas, Ph.D., received his Diploma in EE from NTUA Athens, Greece in 1986, his MSc in CS from the University of Maryland in 1988, and his PhD in CS from the University of Toronto in 1992. He joined the Department of Computer and Information Science, University of Pennsylvania as an Assistant Professor in September of 1992 and was promoted to Associate Professor with tenure in January 1998. From September 2001 he is Professor in the Division of Computer and Information Sciences and the Dept of Biomedical Engineering at Rutgers Univ. Dr. Metaxas is the director of the CBIM (Computational Bio-Imaging and Modeling) Center. He specializes in physics-based modeling techniques with applications to computer vision, graphics, and medical image analysis and has published over 170 research papers in refereed journals and conferences. He is the author of the book ``Physics-Based Deformable Models: Applications to Computer Vision, Graphics, and Medical Imaging''. He has organized several conferences and workshops, is an associate editor of GMIP, and is on the editorial board of Medical Image Analysis. He has received an NSF Career Award (1996), and an ONR Young Investigator Award (1997). He has received 2 best papers awards in computer graphics conferences and a Gold Medal in the Ninth World Congress on Medical Informatics (1998). He is also a Fellow of AIMBE.
Terry S. Yoo is a Computer Scientist in the Office of High Performance Computing and Communications, National Library of Medicine, NIH, where he explores the processing and visualizing of 3D medical data, interactive 3D graphics, and computational geometry. Previously as a professor of Radiology, he managed a research program in Interventional MRI with the University of Mississippi. Terry holds an A.B. in Biology from Harvard, and a M.S. and Ph.D. in Computer Science from UNC Chapel Hill. He has been a speaker and organizer of successful courses on medical visualization and 3D image processing (SIGGRAPH 1993, 1994, 1998, 2001, 2002, Vis 2000, 2001, 2002).
Jannick Rolland, Ph.D.is an Associate Professor of Optics, Computer Science and Electrical Engineering, with a main appointment in the School of Optics and the Center for Research and Education in Optics and Lasers (SoO/CREOL) at the University of Central Florida. Dr. Rolland who is director of the Optical Diagnostics and Applications Laboratory, possesses a unique combination of expertise, including a Ph.D. in Optical Science with a focus in medical imaging research, and 3D visualization using virtual reality methods and innovative technology. Her work is in the area of 3D Optical Imaging and Displays, i.e. optical system design, hardware and software for virtual immersive and augmented environments, objective assessment of the technology, biomedical imaging, texture-based image science, curvature sensing and mathematical modeling. She is a recipient of numerous research awards. She holds B.S. in mathematics and physics from Versailles, France, Diplome d'Ingenieur from l'Ecole Superieure D'Optique, France; and Ph.D. in Optical Sciences from University of Arizona, Tucson.