Medical Image Processing
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.
Catalog DescriptionStudying 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 Processing
Student OutcomesIn the parentheses for each Student Outcome:
"P" for primary indicates the outcome is a major focus of the entire course.
“M” for moderate indicates the outcome is the focus of at least one component of the course, but not majority of course material.
“LN” for “little to none” indicates that the course does not contribute significantly to this outcome.
1. ( Not Applicable ) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics
2. ( Not Applicable ) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors
3. ( Not Applicable ) An ability to communicate effectively with a range of audiences
4. ( Not Applicable ) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts
5. ( Not Applicable ) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives
6. ( Not Applicable ) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions
7. ( Not Applicable ) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.
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.
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