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BIOM5200 / BMG5200 / SYSC5304 / ELG5127 - Medical Image Processing

Description

Mathematical models of image formation based on the image modality and tissue properties. Linear models of image degradation and reconstruction. Inverse problems and regularization for image reconstruction. Image formation in Radiology, Computed Tomography, Magnetic Resonance Imaging, Nuclear Medicine, Ultrasound, Positron Emission Tomography, Electrical Impedance Tomography.

Prerequisites

OCIECE and OCIBME graduate students.

Instructor

Andy Adler ,
Email: adler@sce.carleton.ca ,
Office: Minto 7040 ,
Phone: +1-613-520-2600 x 8785
Office Hours: Office hours will be available by appointment. Please email the instructor to organize a convenient time.

Times and Locations

Winter 2007     (Jan 3 − Apr 6)

Section  Activity  Day  Location 
 
ELG7173B    LEC 1    Monday 11:30 - 13:00    SA 517   
   LEC 2    Wednesday 11:30 - 13:00    SA 505   

Text

There is no assigned text for the course. Lectures will be taken from the following resources:

Marks

Work  Value
Assignments    20%
Project    30%
− Project proposal     − 3%
− Midterm report     − 5%
− Presentation     − 7%
− Report     − 15%
Midterm Exam    25%
Final Exam    25%

Assignments

No.   Assignment   Due Date  
 
1    ELG7173 Assignment #1    Jan. 29   
2    ELG7173 Assignment #2    Feb. 14   
3    ELG7173 Assignment #3    Mar. 14   
4    ELG7173 Assignment #4    Mar. 28   
  • Assignments will be submitted at the beginning of class on the day indicated. Work may be in English or French.
  • While it will be accepted to do programming in any computer language, I recommend Matlab or Octave.
    Access to Matlab is available from almost all PCs in the graduate labs. For home use, you may 1) purchase the student version of Matlab, or 2) use octave (free under the GNU GPL license). Information on installing octave is here.

Project

Activity   Description   Due Date  
 
Project Proposal   Proposal is 1-2 pages (double spaced). Include problem description, proposed techniques, and references.   Feb. 12  
Midterm report   Report is a minimum of 5 pages (double spaced). Describe project progress to date. Discuss any current challenges.   Mar. 12  
Project Presentation   Presentations will be (≤10 minutes) in English. Marks are based on technical content, clarity of presentation, and ability to answer questions.   Apr. 2 − Apr. 4  
Project Report   The report will be 10−20 pages (double spaced) and written in English or French. Include an introduction, methods, results and discussion. Ensure that the report synthesizes and discusses the material. Do not simply restate existing work. Marks are based on the technical content, and clarity of its presentation.   Apr. 11  
  • Students are encouraged to select projects of interest or relevant to their studies. Projects can be
    • A review of a technique or topic
    • An analysis or critique of a technique
    • A comparison between two techniques
    • An implementation or simulation of a technique
  • The following is a rough list of possible project topics:
    −Radiation Detectors
    −Applications of CT
    −Beam hardening and its effects in CT
    −Cardiovascular CT
    −Specialized CT imaging systems
    −Use of a specific contrast agent for CT
    −Problems and limitations of CT for a specific application
    −SPECT applications
    −SPECT image reconstruction algorithms
    −Detectors and technologies for PET
    −Considerations for spatial resolution of PET
    −Specialized PET imaging systems
    −Considerations for 3D PET imaging
    −Problems and limitations of PET for a specific application
    −Design considerations for MRI electronics
    −Design considerations for MRI signal processing
    −Fast MRI: Electronics, Imaging, Applications, etc.
    −Cardiac / Respiratory gated MRI
    −Specialized MRI techniques: Echo planar imaging, etc.
    −Other applications of NMR
    −NMR microscopy
    −Physical limits to NMR resolution
    −Flow MRI
    −MRI of a non-water compound, ie. Xenon
    −Electronics HW and signal processing for EIT
    −Imaging algorithms for dynamic EIT
    −Imaging algorithms for static EIT
    −Problems and limitations of EIT for a specific application
    −Ultrasound for 3D
    −Dopler ultrasound
    −Optical flow techniques for ultrasound
    −Electronics HW and signal processing for ultrasound
    −Problems and limitations of EIT for a specific application
    −Image processing techniques for enhanced visualization
    −Medical image interpretation for specific application
    −Multi-modality image fusion
    −Calibration approaches for multimodality images
    −Virtual Environments applied to medical imaging
    −Automated image classification, search, archiving
    −Applications of expert systems / AI for medical imaging

Exams (Midterm and Final)

  • Midterm exam is Feb. 26 in class. The instructions for the midterm are:
      You have 80 miutes to complete this exam. The exam has four questions; you are required to answer any three of them. Each question is worth equal marks. This is a closed book exam; however, you are permitted to bring one (1) 8.5"×11" sheet of notes into the exam. You are permitted to use a non-programmable calculator. You may not communicate with anyone during the exam except the instructor.
  • Final exam is Apr. 18, 1130−1300
  • For all exams, you will be permitted a calculator and one (1) 8.5" × 11" paper sheet containing any information you choose (double sided).

Marks Policies

  • Late work = 20% off for first week.
  • More than 1 week late = don't bother submitting without good excuse
  • If you wish to do a single (larger) assignments, assignment for two graduate courses, you must obtain written permission from all profs involved. Otherwise, you may find yourself in a position of academic fraud.
  • If you have a question about a mark you have received, fill out, sign and submit this form.
  • Academic fraud will be taken very seriously. Cooperation between students for assignments is expected and encouraged, however, copying of another's work is not. You should not be leaving a discussion with copies of another student's work. Please refer to Carleton Universities policies on this subject. One further note: the excuse of not being aware of the university plagiarism policy is not acceptable.

Students with Disabilities

    Students with disabilities requiring academic accommodations in this course are encouraged to contact a coordinator at the Paul Menton Centre for Students with Disabilities to complete the necessary letters of accommodation. After registering with the PMC, make an appointment to meet and discuss yours needs with me at least two weeks prior to the first in-class test or CUTV midterm exam. This is necessary in order to ensure sufficient time to make the necessary arrangements. Please note the following deadlines for submitting completed forms to the Paul Menton Centre: March 9th, 2007 for the Winter Term.

Course Outline

Date   Activity
Jan 3   Introduction to medical imaging technology
− Notes #1:Intro
− Introduction to Medical Imaging
Jan 8, Jan 10, Jan 15, Jan 17, Jan 22, Jan 24   X-ray imaging. Computed Tomography. Nuclear Medical Imaging, PET, SPECT
− X-Ray Imaging
− Computed Tomography
− Algebraic Reconstruction Technique
− Backprojection
Jan 29, Jan 31, Feb 5, Feb 7   Magnetic Resonance Imaging
Hornak, The Basics of MRI (Chap: 1,3,6,7,8,9)
Notes: Inversion Recovery signal 180-90
at 180 pulse, s0= -[ 1-exp(-(TR-TI)/T1) ], and s(t)= kρ[ 1- (1-s0)×exp(-t/T1)) ]
s(TI)= kρ[ 1- (1+(1-exp(-TR/T1)exp(TI/T1))exp(-TI/T1)) ] = kρ[ 1- 2exp(-TR/T1) + exp(TI/T1))
Feb 12, Feb 14   Perception of images / Human Visual System
Representation of Images / Image Quality and information content
Human visual System
Feb 19, Feb 21   Study Break (No class)
Feb 26   Midterm Exam (in class)
For practice, here are the 2003, 2004, 2005 and 2006 final exams. The midterm reflects the approximately the first two questions in the 2006 final.
Feb 28, Mar 5, Mar 7, Mar 12   Image Enhancement
Removal of Artefacts
− Wiener filters (in the Fourier and Matrix domain
− Histogram Transforms (page 3)
Code to implement histogram equalization: 
m=min(im0(:));M=max(im0(:)); N=255; % or any large number
im1= N*(im0-m)/(M-m);
hv=hist(im1(:),256);
hv= conv2(hv, [.5,.5], 'valid'); %spread weights
map= cumsum(hv);
m=min(map);M=max(map); N=255; 
map= N*(map-m)/(M-m);
im2=reshape( map(floor(im1)+1), size(im0) );
Mar 19, Mar 21   Ultrasound Imaging (Guest lecture by Yuu Ono)
Mar 14,   Regions of Interest
− Marr/Hildreth Edge Detection
− Canny Edge Detection
− Hough Transform, #2 Circular Hough Transform
− Active contours (Snakes)
− Splines
Mar 26 Mar 28   Analysis of Shape / Analysis of Texture
− Erosion, Dilation, Hit-or-miss, Thinning, Skeletonization, Opening, Closing,
− Geometrical Structures
− Fourier Descriptors
− Texture and Applications
Apr 2, Apr 4   Project presentations
Apr 11   Project Reports due (before 16h30)
(or by email with paper copy to follow at exam)
Apr 18   Final Exam. 11h30−13h00 Loeb LA-B149
For practice, here are the 2003, 2004, 2005, 2006, and 2007 final exams, and 2007 midterm exam.
Note that the course content is significantly different from previous years. Thus previous exams should be taken as an indication of my style of exam writing.

Additional Information

Notes (from previous years)

Last Updated: $Date: 2024/01/18 19:40:31 $