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ANNOUNCEMENTS |
This class will next be offered: Fall 2009
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SUMMARY |
Biomedical Imaging (3): Fundamental principles and applications of noninvasive imaging modalities in medicine (X-rays, tomography, magnetic resonance, ultrasound); computer methods and algorithms for image processing, enhancement and analysis.
Class schedule:
Fall Semester, Tue/Thu 5:00 to 6:15 pm in 316 Driftmier
Computer lab: 314 Driftmier
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CONTENTS |
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INTRODUCTION |
Hardly any development in Medical Sciences has revolutionized
medicine as much as the discovery that it was possible to
look into the body without cutting. A hundred years ago, Conrad Wilhelm Röntgen
discovered the X-rays. Since then, noninvasive imaging
of the body literally got a new dimension with the invention
of 3D tomography. CT and MRI allow to acquire cross-sectional
images and to obtain three-dimensional reconstructions of structures.
Two additional modalities will be covered,
positron emission tomography (PET), which allows the imaging of tissue function.
Particularly in conjunction with MRI, it allows new insights in the
function of the brain. Ultrasound is a different modality. It is based
on sound wave reflection, and its advantages are the relatively
inexpensive equipment, and the radiation-free principle.
These fascinating techniques are the topic of this class.
We will look at the physical principles of X-rays and magnetic resonance,
as well as ultrasound imaging. The goal of this class is to understand
physics and technology of those imaging modalities. The second half of the
semester is dedicated to image processing and analysis. Most modern modalities
rely heavily on computer processing of the measured data. Some image processing
methods are inherent to the modality, such as the filtered backprojection
in computed tomography or the Fourier transform of the k-space matrix in MRI.
Of course, the computer can do more than provide the reconstructed images.
Spatial measurements (e.g. the size of an embryo in ultrasound) and density
(e.g. bone mineral density in osteoporosis) can easily be performed. The
computer can also aid in enhancing image quality, suppression of
noise and other artifacts, or in segmenting an object of interest - the
separation of that object from surrounding image regions. The class will
cover the four important steps of image enhancement, segmentation,
quantification, and visualization.
SYLLABUS
BOOKS
Please do not purchase any textbooks at this time!
Textbook: Geoff Dougerty: "Digital Image Processing for Medical Applications",
Cambridge 2009, ISBN 978-0-521-86085-7
Note: We are going to loosely follow the book. This textbook is
rather intended as further reading and support than a strict textbook.
Recommended further reading:
Essential Physics of Medical Imaging
The Image Processing Handbook
Digital Image Processing - Principles and Applications
Digital Image Processing Algorithms and Applications
Magnetic Resonance Imaging: Physical Principles and Sequence Design
COMPUTER LAB
GRADING
The grade will be based about equally on the homeworks, the midterm
exam, and the final exam.
You will receive score points based on the fill-the-bucket principle,
i.e. for each homework assignment and for each test, you accrue score points.
Your final grade will be determined from the score you achieved relative
to the maximum score achievable. Typically, you receive a maximum of 20
points per homework, and 100 points per test,
resulting in a maximum score of around 300 points.
We use a fixed grading system. There will be no adjustment
based on the overall class performance.
The following table shows the percentage of your score you need to reach
for a specific grade:
RESOURCES
Click here to enter the resources page.
On this page, you will find items for download, such as the Scion Image
program and photocopied texts. You will have to obtain the password
for CSEE 4620 in order to access this page.
OFFICE HOURS
Office hours TBD or by individual appointment
in my office 404 Driftmier.
HOMEWORKS
LINKS
Here is a collection of some links I found interesting:
ABET Information
Lecture block Topic
1 Introduction to Biomedical Imaging
History and development of Biomedical Imaging
2 X-rays: Physics and instrumentation
X-ray tubes, detectors, X-ray attenuation in tissue
Film, image intensifiers, detectors
3 Quantitative X-ray imaging
4 The Fourier transform
5 Computed Tomography: Principles
Reconstruction algorithms
Instruments and aplications
6 MRI: Physical foundations
Precession and spin echo
Gradient encoding
image reconstruction
7 Image processing: Fundamentals
Image representations:
from matrices to false-coloring
8 Filtering concepts (1) The convolution operation
9 Filtering concepts (1) Convolution filters
Convolutions. Smoothing, sharpening, background removal
Laplacian, Robert's Cross, Kirsch, Sobel, Canny edge, Frey and Chen
10 Filtering concepts (3) Fourier filters
Fourier transformation; spectrum interpretation
Lowpass and highpass filters
11 Filtering concepts (4) Morphological operators
Rank filter; erosion, dilation, opening, closing; skeletonization
12 Statistical representation of images
Histogram manipulation
13 Segmentation methods
Basic thresholding
14 Segmentation methods
Automated thresholding
Region growing & the Watershed transform
15 Image quantification
Density and size quantification
Shape quantification
by G. Bushberg
Lippincott Williams & Wilkins
This textbook covers all aspects of medical image acquisition. Presents an
understanding of the theory and applications of the science including basic
concepts, X-ray imaging, ultrasound, MRI, nuclear medicine, radiation
protection, radiation dosimetry, and radiation biology. Abundant illustrations.
This book is directed at students with a medical background.
by John C. Russ
CRC Press
A very comprehensive and extensive book covering all aspects of image
processing in Engineering and Science. Unfortunately, this comes at
a relatively high price.
by Gregory A. Baxes
Less extensive than the book by John C. Russ, but still comprehensive, it
covers the major aspects of image processing. Highly recommendable if you
have an interest in image processing and analysis.
by Ioannis Pitas
Wiley-Interscience
This book is a good reference for those of you who are
interested in actually programming those algorithms. It provides
lots of C source code.
by E. Mark Haacke, Robert W. Brown, Michael R. Thompson, Ramesh Venkatesan
John Wiley & Sons
For those of you who really want to get into MRI, this book provides
even more in-depth MRI knowledge, covering the special area of sequence design
for specific medical and research applications
Grade Minimum percentage
Grade Minimum percentage
Grade Minimum percentage
A+ 96%
A 93%
A- 90%
B+ 85%
B 80%
B- 75%
C+ 70%
C 65%
C- 60%
D+ 50%
D 45%
The best way to contact me is by email.
The individual homework assignments
No. Homework Date assigned Date due Maximum Score
1
The Fourier Transform
9-3-09 9-10-09 15
2
Computed Tomography
9-17-09 10-01-09 20
3
Magnetic Resonance Imaging
10-06-09 10-13-09 20
4
Spatial-Domain Filters
11-05-09 11-12-09 20
5
Segmentation
11-19-09 12-03-09 35
| Course Learning Objectives | Relationship to ABET criteria |
| Upon succesful completion of this course, the student will be able to | The objective relates to the ABET criteria strongly:3, moderately:2, marginally:1, not at all:0 |
| Understand the image formation process (physics and engineering aspects) of different imaging modalities |
a:3, b:0, c:0, d:0, e:1, f:0, g:0, h:1, i:0, j:0, k:0 |
| Understand computer algorithms that are used in image formation and image reconstruction | a:3, b:0, c:0, d:0, e:2, f:0, g:0, h:1, i:0, j:0, k:0 |
| Understand computer algorithms that are used to further enhance or analyze images | a:3, b:0, c:3, d:0, e:2, f:0, g:0, h:1, i:0, j:0, k:0 |
| Understand the medical and societal impact caused by noninvasive diagnostic methods based on imaging | a:0, b:0, c:0, d:0, e:0, f:0, g:0, h:2, i:0, j:0, k:0 |
| Understand current trends of medical imaging by being exposed to topical literature | a:0, b:0, c:0, d:0, e:0, f:0, g:0, h:2, i:0, j:3, k:0 |
| Apply their knowledge on medical or nonmedical sample images in small lab-based projects | a:3, b:2, c:3, d:1, e:2, f:0, g:0, h:1, i:0, j:0, k:0 |
| Design a complete image analysis chain and implement it in a major lab-based project | a:3, b:2, c:3, d:1, e:3, f:0, g:2, h:1, i:0, j:0, k:0 |
Overall Course Contribution to Program Outcomes:
a: extensive
b: extensive
c: moderate
d: moderate
e: extensive
f: marginal
g: moderate
h: moderate
i: marginal
j: moderate
k: moderate