Medical Image Reconstruction


[Under Construction]

Grad Student Info
Class Info
Useful Links

Final Project Statement (Oral Exam: Saturday May 29, 2010 starting at 3:30p)


1. No questions on the exam statement will be allowed. Assume any missing information and interpret the question the way that simplifies your answer.

2. Please provide your answers as a PDF file to be turned in during your oral exam and be prepared to run your code for any part of your answers.

3. You are not allowed to discuss the project problems with your colleagues. You may use any literature, web, or other resources as long as you use proper reference citation.

4. Check on the homework submission excel sheet below that your last version of your homework solution has been received for each assignment.

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Administrative Information

Class meeting times: Saturdays at 5:15p - BME 3201 auditorium

Attendance is required for all lectures - Attending 85% of classes is required to pass the course NO EXCEPTIONS

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Intended Learning Objectives (ILOs)

To build a strong theoretical and practical implementation skills for medical image reconstruction. This is an advanced course and therefore will cover advanced topics immediately from the start.

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A number of sources from textbooks and research papers will be handed out for each lecture

1. Handout #1: Reference for lecture 1

2. Handout #2: Reference for interlaced Fourier transform of lecture 3

3. Handout #3: References for Shepp-Logan phantom of lecture 3

4. Handout #4: References for gridding problem of lecture 4

5. Handout #5: Extra reference for lecture 4 (not included in exam)

6. Handout #6: Reference for lecture 5

7. Handout #7: Reference for analytical Fourier transform of the Shepp-Logan phantom.

8. Handout #8: Reference for partial Fourier reconstruction for lecture 6.

9. Handout #9: Reference for reconstruction under in-plane motion of lecture 7.

10. Handout #10: Reference for ultrasound imaging of lecture 8.

11. Handout #11: Reference for synthetic aperture ultrasound imaging of lecture 8.

12. Handout #12: References for Compressed Sensing for lecture 9.


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Grading Policy

100% on Class Projects and Final Project

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Course Topics to be Covered

  1. Mathematical basis
  2. Image reconstruction in MRI/CT: reconstruction from nonuniformly sampled k-space.
  3. Image reconstruction in MRI: partial Fourier methods.
  4. Image reconstruction in MRI: Reconstruction under motion
  5. Reconstruction in other modalities: Ultrasound synthetic aperture imaging reconstruction
  6. Compressed sensing theory and applications

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Lecture Presentations

1. Lecture #1 and #2 presentations (February 27 and March 6, 2010).

2. Lecture #3 presentation (March 13, 2010).

3. Lecture #4 presentation (March 20, 2010).

4. Lecture #5 presentation (March 27, 2010).

5. Lecture #6 presentation (April 3, 2010).

6. Lecture #7 presentation (April 10, 2010).

7. Lecture #8 presentation (April 24, 2010).

9. Lecture #9 presentation (May 08, 2010).


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Exercises (for Coursework Grades)


List of all problem assignments for all lectures        Updated May 6, 2010


(Grading policy: coursework grades = sum of points of all correctly solved assignments delivered on time + half of sum of points of all correctly solved assignments delivered late)


List of Received Homework solutions from each student     Updated May 27, 2010


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Data Samples


1. Radial sampling of the analytical Shepp-Logan phantom

(text file, target image size should be128x128, each row is one sample, four numbers on each row for normalized (kx,ky) and their complex k-space data value, format: "kx value"  "ky value"  "real part of k-space" "imaginary part of k-space").


2. Full k-space data of a real image of transverse slice of a normal human brain for partial Fourier reconstruction data.      (Download sample Matlab reading program here)

(text file, k-space size: 256x256, each row is one sample with real and imaginary parts, 2D k-space written in sequence row by row)


3. Synthetic aperture ultrasound data sets

(each is written in binary form - information about organization of data is included inside each archive - choose one archive only to work on)




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Last modified: February 14, 2012