| Instructor(s) | Arman Aghaee [Coordinator] Office: EPH426 Phone: TBA Email: arman.aghaee@torontomu.ca Office Hours: Fridays 10 AM - 11 AM | ||||||||||||
| Calendar Description | Introduces the fundamental principles of medical image analysis and visualization. Focuses on the processing and analysis of ultrasound, MR, and X-ray images for the purpose of quantification and visualization to increase the usefulness of modern medical image data. Includes image perception and enhancement, 2-D Fourier transform, spatial filters, segmentation, and pattern recognition. | ||||||||||||
| Prerequisites | BME 229 and BME 772 | ||||||||||||
| Antirequisites | None | ||||||||||||
| Corerequisites | None | ||||||||||||
| Compulsory Text(s): |
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| Reference Text(s): |
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| Learning Objectives (Indicators) | At the end of this course, the successful student will be able to:
NOTE:Numbers in parentheses refer to the graduate attributes required by the Canadian Engineering Accreditation Board (CEAB). | ||||||||||||
| Course Organization | 3.0 hours of lecture per week for 13 weeks | ||||||||||||
| Teaching Assistants | TBA | ||||||||||||
| Course Evaluation |
Note: In order for a student to pass a course, a minimum overall course mark of 50% must be obtained. In addition, for courses that have both "Theory and Laboratory" components, the student must pass the Laboratory and Theory portions separately by achieving a minimum of 50% in the combined Laboratory components and 50% in the combined Theory components. Please refer to the "Course Evaluation" section above for details on the Theory and Laboratory components (if applicable). | ||||||||||||
| Examinations | Midterm exam covers all material covered in class up until the examination. Midterm is scheduled for week 7. The final exam will cover all course material. | ||||||||||||
| Other Evaluation Information | Laboratory: All labs require final write-ups and submission of working code to generate your results. Requested analysis, images and information that will be assessed are included in the lab description. During lab times, the TA will ask you to demo your code, and ask questions about its operation and the results. Labs will be demonstrated to the TA during the last week of the lab and lab reports will be due that same week. Images and experimental details will be given on the course website. The lab work is individually. The labs will consist of theoretical and practical parts and will require the use of Matlab. | ||||||||||||
| Other Information | None | ||||||||||||
Week | Hours | Chapters / | Topic, description |
|---|---|---|---|
1 | 3 | Class Notes | Introduction to Medical Images/Imaging |
2 | 3 | Chapter 1 & Chapter 2 | Introduction to Digital Image Processing & Digital Image Formation |
3-4 | 4 | Chapter 5 | Enhancement Denoising |
4-6 | 7 | Chapter 10 | Segmentation (Intro to Classification) |
7 | 2 | Midterm | Midterm covering lectures 1-6 |
8-9 | 5 | Class Notes | Abnormality Extraction-Detection |
10 | 3 | Class Notes | Registration |
11 | 3 | Class Notes | Landmarks Extraction |
12 | 3 | Class Notes | Interpolation |
13 | 3 | Class Notes | Compression |
Week | L/T/A | Description |
|---|---|---|
2-4 | LAB 1 | Fundamentals of Medical Image Representation, Enhancement, and Restoration |
5-7 | LAB 2 | Spatial and Frequency Domain Filtering, Edge Detection, and Morphological Processing |
8-10 | LAB 3 | Image Restoration, Inverse Problems, and Advanced Denoising Algorithms |
2-12 | LAB 4 | Image Segmentation using Pixel Classification, Clustering Algorithms, and Statistical Models |
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