Our areas of research range from image acquisition to image analysis to image application. These are some suggestions for courses that are available in our many fields.
A curriculum for each student can be tailored around their background and interests in order to focus on two of the three educational cores in Translational Imaging: medical physics and imaging, biomedical imaging applications, and biomedical image analysis.
The medical physics and imaging core is designed to provide knowledge about the underlying physics and instrumentation necessary to acquire images. Existing and planned courses in this area are indicated in Table 1.
Medical Imaging Systems
Modern Biomedical Imaging
Magnetic Resonance in Medicine
Herzka, Fall (even years)
Seminar on Advanced Topics in MRI Research
Biomedical Optical Imaging
Li, Spring (odd years)
Molecular and Cellular Imaging
Bulte et al, Spring
Table 1 Courses in BME and ECE that address medical physics and imaging core topics available at this time
Biomedical Imaging Applications
The biomedical imaging applications track is designed to provide knowledge about current practices in radiology, interventional therapy, and neuroscience, with emphasis on organ systems and the imaging techniques that are called upon for diagnosis, treatment, and scientific discovery. Course that exits currently are shown in Table 2. Xingde Li and Jeff Siewerdsen (new BME faculty) will be developing 2 new courses in the applications of optical and xray techniques in image guided procedures. Dan Herzka (new BME faculty) will be designing a new course in advanced MRI pulse sequence design.
Intro to Comput.-Integrated Surgery
Thakor, fall and spring
Computer-Integrated Surgery I
Projects in Applied Medical Imaging
Computer Integrated Surgery II
Table 2 Courses in BME and CS that explicitly address biomedical imaging applications
Biomedical Image Analysis
The biomedical image analysis track is designed to provide knowledge about methods for the analysis of biomedical images. There is a rich collection of courses offered within various engineering departments that will serve this purpose, as indicated in Table 3.
Image Processing and Analysis I
Image Processing and Analysis II
Image Recon. and Restoration
Advanced Topics in Comput. Vision
Statistical Methods in Imaging
Computer Vision Seminar
Medical Image Analysis
Information, Statistics, and Perception
Mathematical Image Analysis
Pattern Theory: From Representation to Inference
Computer Vision Seminar
Medical Image Analysis Seminar
Table 3 Courses in BME and CS and ECE that explicitly address biomedical image analysis
Additional courses may be required as prerequisites or for broader knowledge. Typical courses that may serve this purpose are provided in Table 4.
Foundations of Optimization
Goldman, Han, fall
Goldman, Han, spring
Introduction to Real Analysis
Random Signal Analysis
Table 4 Courses available in the engineering school giving students a strong mathematical foundation
The ICTR faculty offer an intensive two week course each summer in which students study the techniques of clinical trial design and methods for measuring clinical effectiveness. This is a key component for students to understand how new imaging modalities should be evaluated, and the costs associated with that evaluation. This training will also all allow the students to determine which imaging technique would be most effective as a surrogate endpoint for clinical trials. This will often require a re-design of existing imaging techniques and is an vital component for the participation of imaging scientists in reducing the cost of clinical trials.
Introduction to Clinical Research:
A Two-Week Intensive Course
ICTR faculty, summer
Table 3.C.4.5 Course in which students can become trained in the techniques of clinical trials and translation. For a syllabus of this course, see the letter of support from Dr. Daniel Ford, Director of the Institute for Clinical and Translational Research.
Biomedical Image Analysis Track
The following example illustrates the curriculum for Bennett Landman, who received his PhD in Biomedical Engineering in 2007. He is now an Assistant Professor in BME at Vanderbilt University. Bennett’s research involved a collaboration with Michael Miller, Jerry Prince, and Susumu Mori on using diffusion weighted MRI for fiber tracking in the brain. His course selection was customized to give him the required mathematical background, accompanied by a firm foundation in physiology and MRI.First Year:
Medical School (including developmental systems, neuroscience and anatomy)Second Year, Fall:
Matrix analysis, Statistical Theory I, Magnetic Resonance in MedicineSecond Year, Spring:
Statistical theory II, Statistical Methods in Imaging, Advanced Topics in MRIThird Year:
TA: Statistical Methods in Imaging
TA: Signals and Controls