ELEC ENG 4BF3

Medical Image Processing

Academic year 2007-2008, term 2

Instructor: Xiaolin Wu, ITB-A315

Extension: 24190

Email: xwu@ece.mcmaster.ca

Teaching Assistant: Huazhong Wang, Minkai Shao

ITB-A103

Lectures: 2 hours/week

Tutorial: 1 hour/week

Laboratory: 2 hours/week

Final Exam Date: April 26 (Saturday), 9~11 am. Close book.

Place: ITB/A113B and ITB/AB105.

Slides: Lecture1_Modalities, Lecture2_Fundamentals, Freq_enhancement, Enhance_spatial.pdf, Modalities.pdf, Segmentation.pdf, Morphology.pdf,

lecture5_restoration.pdf, measurement.pdf, Visualization.pdf, ultrasound.pdf, registration.pdf, Compression1.pdf, Compression2.pdf, Wavelet Transform.ppt, lecture6_wavelet.ppt

Project site: http://grads.ece.mcmaster.ca/~wanghz/4bf3/

Assignment 1:

• Questions 3.12, 3.18, 4.2, 4.12 in the text book.

Due date: February 25.

Assignment 2:

• Derive the interpolation coefficients a, b, c, and d in Equation (5.11-7) of page 273 of the textbook, also on page 55 of the lecture notes.

Due date: March 14.

Sample questions for midterm:

• Dilation and erosion for gray-level image is a generalization of the same operations in binary images. Describe how they are done.
• An image of 20 grey levels has the histogram [0,100,200,300,500,600,500,300,200,100,200,500,3000,8000,20000,8000,3000,500,100,0]. The image has one fruit in a contrasting background. The pixel spacing is 2mm. Is the fruit a cherry, a grapefruit, or a pumpkin?
• What does the skeleton of two touching filled circles look like?
• The questions in Assignment 1.

The midterm exam time and place: ITB/A113B, Feb. 27, 7 – 9 pm.

Midterm Coverage: Fundamentals, mathematical morphology, spatial domain enhancement, and frequency domain enhancement.

Course Outline:

Course Objectives:

• Introduce basic concepts and methodologies for the formation, representation, enhancement, analysis and compression of digital medical images.
• Establish a foundation for developing applications and for research in the field of medical image processing.
• Provide training for the design and implementation of practical algorithms for medical image processing.

Outline of Topics:

· Introduction

o Applications of medical image processing

o Elements of medical image processing system

· Digital Image Fundamentals

o Image perception

o Sampling and quantization

o Basic relationships between pixels

· Image Enhancement

o Point processing

o Spatial filtering

o Frequency domain method (slides)

· Image Restoration

o Degradation models

o Inverse filtering

o Minimum mean square error (Wiener) filtering

o Constrained least squares filtering

· Wavelets and multiresolution processing

o Multiresolution expansion

o Wavelet transforms in one dimension

o Wavelet transforms in two dimensions

· Image Compression

o Elements of information theory

o Lossless compression

o Lossy compression

o Image compression standards

· Image Segmentation

o Detection of discontinuities

o Segmentation by thresholding

o Region based segmentation

· Image representation and description

o Chain codes

o Fourier descriptors

o Moments

o Color image processing

o Color models

o Pseudocolor image processing

o Color transformation

o Morphological image processing

o Dilation and erosion

o Opening and closing

o Hit or miss transformation

Format: The course consists of class lecture sessions, tutorial session and a laboratory component. The lab component of the course consists of programming assignments and a small project that students can do on their own time schedule.

Assessment:

Homework and/or Quiz: 10%

Midterm: 20%

Final: 40%

Project: 30%

Calculator requirement for tests and examinations: any calculator is allowed.

Textbook:

“Digital Image Processing, Second edition”, by R. Gonzalez and R. Woods, Prentice Hall, 2002.

Reference books:

“Medical Image Analysis”, by Atam P. Dhawan, Wiley Inter-Science, 2003.

“Digital Image Processing”, by K. R. Castleman, Prentice-Hall, 1996.