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ECE Course Syllabus

ECE6780 Course Syllabus


Medical Image Processing (3-0-3)

Technical Interest
Bioengineering,Digital Signal Processing



Catalog Description
Studying biomedical image analysis techniques including image enhancement, analysis, classification, and interpretation for medical decision-making through practicals and projects. Cross-listed with BMED6780.

Gonzales, Digital Image Processing (4th edition).(optional)

Indicators (SPIs)
SPIs are a subset of the abilities a student will be able to demonstrate upon successfully completing the course.

Outcome 1 (Students will demonstrate expertise in a subfield of study chosen from the fields of electrical engineering or computer engineering):
Upon successful completion of the course, the student should be able to demonstrate the ability to formulate biomedical image analysis pipeline for medical decision support.  

Outcome 2 (Students will demonstrate the ability to identify and formulate advanced problems and apply knowledge of mathematics and science to solve those problems):
Upon successful completion of the course, the student should be able to apply mathematic knowledge and programming techniques to perform biomedical image analysis for medical decision support.  

Outcome 3 (Students will demonstrate the ability to utilize current knowledge, technology, or techniques within their chosen subfield):
Upon successful completion of the course, the student should be able to demonstrate oral and written communication ability to report biomedical image processing problem-solving. 

Topical Outline
1. [3 hrs]   Biomedical Image Analysis: Motivation; Importance; and Challenges.
2. [1.5 hrs]   Medical Image Formation: Imaging Modalities (X-Ray, MRI, PET, SPECT, Ultrasound); and Comparison of Data Resulting from Different Modalities. 
3. [1.5 hrs] Biomedical Imaging for Diagnosis Decision Support: Quality Metrics, Grey Images and Color Images Formation; and Visualization.
4. [4.5 hrs] Image Enhancement: Intensity Data Histogram Modeling; Thresholding; Signal-to-Noise Characteristics; Fourier Transformation; Color Transformation. 
5. [1.5 hrs] Image Analysis: Edge Detection; Contour Tracing; Segmentation.
6. [9 hrs] Image Interpretation: Feature Extraction; Pattern Recognition; Classification; Interactive Decision Support
7. [18 hrs] Practical and Project: Analyzing Real-World Biomedical Image Data for Clinical Decision Support
8. [3 hrs]  Technical Presentations of Critical Thinking in Projects Design, and Software Design of Biomedical Image Data Analysis. 
9. [3 hrs] Exams