Fundamentals of Medical Imaging
Friday 13h00 to 16h00 in CSC 363
The course starts by reviewing signal processing theory with example from medical imaging. We will then study six general medical imaging modalities: projection radiography, computed tomography, magnetic resonance imaging, nuclear imaging, ultrasound, and confocal microscopy. The goal will be to understand these modalities in terms familiar to medical practitioners. Following the study of modalities, we will then review basic 3D image processing such as filtering, registration, segmentation, and data driven physical simulation. Flexibility exists for the instructor to vary the depth of each topic area after determining the general background and experience of the students.
Lecture 1: History of Modalities:
Lecture 2: Basics of Linear Systems:
Lecture 3: Convolution and 1-D Fourier Transform:
· Assignment 2 (Due Sept. 26)
Lecture 4: 2-D Fourier Transform:
Lecture 5: Sampling Theorem:
Lecture 6: Discrete Fourier Transform:
Lecture 7: Hankel Transform:
Lecture 8: 3-D Slicer
Lecture 9: Fundamental of X-Ray Physics-I:
Lecture 10: Fundamental of X-Ray Physics-II:
Lecture 11: X-Ray Distortion and Non-linearity:
Lecture 12: Statistical Model of X-Ray Images:
Lecture 13: X-ray CT-I:
Lecture 14: X-ray CT-II:
Lecture 15: Fundamental of MR:
Lecture 16: MRI Image Formation Overview:
Lecture 17: Nuclear Imaging:
Lecture 18: Ultrasound Imaging Systems:
· Powerpoint files: Ultrasound.ppt
Lecture 19: Fluoroscopy and Confocal Microscopy
· Powerpoint files: Confocal.ppt
Lecture 21: Multi-modal Non-linear Filtering
· Powerpoint files: Filtering.ppt
Lecture 22: Multi-modal Registration
· Powerpoint files: Registration.ppt
· Assignment 6 (This is a supplementary assignment and it is voluntary)
Lecture 23: Multi-modal Segmentation
· Powerpoint files: Segmentation.ppt
Lecture 24: From Segmentation to Physical Simulation and Surgical Planning
· Powerpoint files: Simulation.ppt
· Assignment 7 (This is a supplementary assignment and it is voluntary)
The following textbook is used to provide both the engineering, mathematical, and physics background necessary for this course. I will lecture from the class notes but I will refer to the textbook from time to time and some of the assignment will be from the textbook.
J.L. Prince and J.M. Links, Medical Imaging: Signals and Systems, Pearson Prentice Hall Bio-engineering
Homework will generally be handed out during a lecture and will be due on the following week. Some parts of the homework may involve SLICER exercises. There will be 6 problem sets. Don't be misled by the relatively few points assigned to homework grades in the final grade calculation. While the grade that you get on your homework is at most a minor component of your final grade, working the problems is a crucial part of the learning process and will invariably have a major impact on your understanding of the material.
There will be an individual semester project, culminating in a final 8 pages report in IEEE format and a 20 minutes presentation during a one day workshop in December. Progress and check points before the final due date will count toward the final grade.
The final grade for the course is based on our best assessment of your understanding of the material, as well as your commitment and participation. The SLICER project, problem sets, and the final projects are combined to give a final grade:
· Introduction to various technologies from HowStuffWorks.com
· Joseph Hornak, The Basics of MRI
· Online resource, available at http://www.cis.rit.edu/htbooks/mri/ (Introduction to MRI)
· The Visible Human Project
· Interactive Visible Human Viewer
· The Computer Vision Test Image Database has many databases relevant to image processing. Some contain medical images
· The MedPix Database has X-ray and CT and MRI images.
· digimorph.org X-Ray CT views of living and extinct vertebrates.
· P. K.Kaiser; The Joy of Visual Perception, Online book, 1996.
· Kak, M. Slaney. Principles of Computerized Tomographic Imaging, Society of Industrial and Applied Mathematics, 2001.
· Martin Spahn Flat detectors and their clinical applications Eur Radiol (2005) 15: 1934-1947