This document outlines the course details for Medical Image Processing at Yarmouk University, including the instructor's contact information, pre-requisites, course description covering fundamental image processing techniques, expected learning outcomes, objectives, topics to be covered in classes, required textbooks, grading criteria based on exams and homeworks, attendance policy, and expectations for academic integrity. The course introduces students to basic and advanced image processing algorithms applied to medical images from modalities like MRI, CT, and PET through lectures, projects, and exercises in MATLAB.

1. Yarmouk University Medical Image Processing,
Course
Hijjawi Faculty for Eng. Tech. BME 544
BME and MI Department Instructor Dr. Awad Al-Zaben
Term Fall 2010
Sunday, Tuesday, Thursday,
Meetings
10:00-11:00
Instructor’s Contact Information
Office Phone 4552
Other Phone -
Office Location Room 503
Email Address azaben@yu.edu.jo
Office Hours Will be assigned
General Course Information
Pre-requisites,
BME 390
Co-requisites
Fundamental concepts of low and high level image processing algorithms
used in medical image analysis (such as those that occur in MRI, CT, PET or
SPECT imaging). A basic review of image acquisition, through low level
Course
processing to high level object extraction and recognition: Image
Description
enhancement, restoration, filtering, segmentation, morphology, texture,
presentation & description, compression, recognition & interpretation, and
registration. These topics will be demonstrated throughout projects.
In learning the course topics, the student will attain the following outcomes:
1. Understand the frequency domain description of discrete-time image
processing.
2. Understand the design & specification of multi-dimensional digital filters
for medical image processing applications.
3. Gain proficiency in using simulation and design software tools, such as
Course Outcomes
those found in Matlab, MeVisLab
4. Aware of contemporary applications of image processing in medical image
analysis (such as those that occur in MRI, CT, PET or SPECT imaging).
5. Apply the concepts of Image enhancement, restoration, filtering,
segmentation, morphology, texture, and registration to the output medical
images.
1.To introduce students to basic image processing techniques in
analyzing biological images.
2.To develop the students mathematical, scientific, and computational
Course Objective
skills relevant to the field of biomedical image processing.
3.To enhance the students ability in formulating problems and
designing analysis tools for biological image.
1. Digital Image Processing Using MATLAB, Rafael C. Gonzalez,
Required Text
Richard E. Woods, Steven L. Eddins. Prentice Hall, 2003.
2. Handout.
1. Medical Image Processing, Reconstruction and Restoration, Jiri
References
Jan, Taylor & Francis Group, 2006.
2. Biosignal and Biomedical Image Processing, MATLAB Based
Applications, John L. Semmlow. Publisher: Marcel Dekker, Inc.

2. Publication year 2004.
3. Isaac N. Bankman, Handbook of medical imaging, Acadmic Press,
2000
4. Rafael C. González, Richard Eugene Woods, Digital image processing.
Prentice Hall, 2002.
Schedule
 Fundamentals
 Intensity Transformations and Spatial Filtering
 Frequency Domain Processing
 Image Restoration
Topics  Wavelets
 Morphological Image Processing
 Image Segmentation and Fusion
 Image Transformations and Registration
 Image Reconstruction
Course Policies
First Exam 20%
Second Exam 20%
Grading Criteria Final Exam 50%
Homeworks 10%
In accordance with the University Regulations, it is the student responsibility
to be punctual and to attend all classes.
Class Attendance An absentee withdrawal notice will be issued and the student will be deemed
to have withdrawn from the course if a student is absent for more than 15%
of the total contact hours.
The department expects from its students a high level of responsibility and
academic honesty. Because the value of an academic degree depends upon
the absolute integrity of the work done by the student for that degree, it is
Academic imperative that a student demonstrate a high standard of individual honor in
Integrity his or her scholastic work.
Any student who commits an act of scholastic dishonesty is subject to
University lows.