Department of Computer Science
University of New Mexico
CS 491/591 Computational Medicine
Fall, 2004
Instructor: Dr. Shuang (Sean) Luan
Coordinates:
Email: sluan@cs.unm.edu
Office: 345G Farris Engineering Center (FEC)
Phone: 505-277-9620
Office Hours: MW 2:00pm-3:00pm
Class Meeting Times: MWF 12:00pm-12:50pm
Class Room Location: 329 Dane Smith Hall (DSH)
Prerequisite and Background: No formal background,
however mathematical maturity and some basic algorithms design and analysis
skills are expected.
Textbook: None. (Reading materials will be distributed
in class.)
Useful References:
Thomas H. Cormen, Charles E. Lerserson, Ronald L. Rivest,
and Clifford Sterin, Introduction to Algorithms, 2nd edition, the MIT
Press.
Ravindra K. Ahuja, Thomas L. Magnanti, James B. Orlin, Network
Flows: Theory, Algorithm and Applications, Prentice Hall
Jorge Nocedal and Stephen J. Wright, Numerical
Optimization, Springer
Henry Stark and John W. Woods, Probability, Random
Processes, and Estimation Theory for Engineers, 2nd Edition, Prentice Hall
Urmila M. Diwekar, Introduction
to Applied Optimization, Kluwer Academic
Frank H. Attix, Introduction to Radiological Physics and
Radiation Dosimetry, Wiley-Interscience
Carlos A. Perez, Luther W. Brandy, Edward C. Halperin, and
Rupert K. Schmidt-Ullrich, Principles and Practice of Radiation Oncology,
4th edition, LIPPINCOTT WILLIAMS & WILKINS
Jerrold T. Bushberg, J. A. Seibert, Edwin M. Leidholdt, Jr.,
and John M. Boone, the Essential Physics of Medical Imaging, 2nd
edition, LIPPINCOTT WILLIAMS & WILKINS
Rafael
C. Gonzalez and Richard E. Woods, Digital Image Processing, 2nd
edition, Addison-Wesley
Albert
MacOvski, Medical Imaging Systems, 1st edition, Pearson
Education POD
Eric
Hall, Radiobiology for the Radiologist, 5th Edition, Lippincott
Williams & Wilkins
Course
Objective:
The
main goal of this course is to promote analytical thinking through the
introduction of new application domains. Therefore, the emphasis is not on the
medical knowledge or the specific applications, but is on the ability of
modeling and solving practical problems using previously gained knowledge in
other fundamental subjects.
Topics:
Theory:
- Graph
algorithms (shortest path, matching, flows, etc)
- Probability
and statistics (Bernoulli trials, Poison distributions, etc)
- Monte
Carlo methods
- Convex
programming (linear programming, Newton's method, etc)
- Applied
optimization techniques (integer programming, simulated annealing, etc)
Application:
- Basic
radiological physics
- Basic
radiobiology
- Radiation
therapy planning
- Medical
imaging
Works
Expected from Students:
- Class
attendance is required.
- Homework
and presentations.
- One
final exam or project.
The
instructor reserves the right to replace the final exam with a final
presentation.
Grading:
- Homework
and 2 semester projects (75%)
- Class
attendance (5%)
- Final
exam or final project (20%)
The
instructor reserves the right to make minor changes to the above grade
distribution (e.g., in the event of replacing the final exam with a final
presentation).
The
following grade break down will be used:
- 90-100
= A; 85-90 = A-; 80-85 = B+; 75-80 = B; 70-75 = B-; 65-70 = C+; 60-65 = C;
0-59 = F
The
instructor reserves the right to adjust borderline grade up and down based on
other subjective criteria.
Course
Policies:
- Late
homework: homework must be turned in at the beginning of the class period.
Submission turned in up to 48 hours later will incur a 20% grade penalty.
Submission turned in past 48 hours will be graded 0.
- Excused
absences due to personal reasons or approved University travel must follow
university policy. In the case of foreseen absence, instructor must be
informed prior to the absence date.
- Academic
honesty: the University of New Mexico Student Code of Conduct, item 2.4 on
academic dishonesty will strictly observed. Details of the Student Code of
Conduct can be found in the UNM Student Handbook.
Lecture
Notes:
Please visit the UNM WebCT page for lecturenotes, homework, and project announcements
Acknowledgment:
Ross Berbeco, Massachusetts General Hospital and Harvard Medical School
Warren D'Souza, Department of Radiation Oncology, University of Maryland
School of Medicine
Phil Heintz, Department of Radiology, University of New Mexico
Paul Keall, Virginia Common Wealth University
Hongchao Liu, University of Notre Dame
Daniel Low, Washington University School of Medicine
Lijun Ma, Department of Radiation Oncology, University of Maryland School
of Medicine
Shahid Naqvi, Department of Radiation Oncology, University Maryland School
of Medicine
Mehrdad Sarfaraz, Department of Radiation Oncology, University of Maryland
School of Medicine
Juong Rhee, Department of Radiation Oncology, University of Maryland School
of Medicine
Dave Shepard, Department of Radiation Oncology, University of Maryland
School of Medicine
Cedric Yu, Department of Radiation Oncology, University of
Maryland School of Medicine