Medical Image Processing
(3-0-0-3)
CMPE Degree: This course is Not Applicable for the CMPE degree.
EE Degree: This course is Not Applicable for the EE degree.
Lab Hours: 0 supervised lab hours and 0 unsupervised lab hours.
Technical Interest Group(s) / Course Type(s): Bioengineering, Courses for non-ECE majors, Digital Signal Processing
Course Coordinator:
Prerequisites: ECE2026
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.Textbook(s)
Digital Image ProcessingCourse Outcomes
Not Applicable
Strategic Performance Indicators (SPIs)
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