Course Overview

Image processing is a basic tool for biomedical image analysis. Ranging from contrast enhancement to stereotatic surgery, image processing provides various levels of assistance to the biomedical researches and clinical applications. As an introductory course to the biomedical image processing, the aim of this course is to offer the entry-level graduate students the fundamental image processing techniques. The scope of this course will cover the basic transformation techniques, properties of various medical images, image acquisition, processing and rendering. In addition to the regular lectures, the students are required to exploit advanced techniques independently to reinforce learning. It will include one term project and a couple of paper studies. Actual implementation of the image processing algorithms on the biomedical images will be emphasized in this course. Although it is not a pre-requisite, the students need to use Matlab as the programming tool for the homeworks. There will be about five homeworks for practice. One exam will be given toward the end of the class. The students will be asked to demonstrate the result of the term project by an oral presentation and a written report. Topics l Basic Transformation Techniques l Basics of Medical Images l Image Acquisition, Sampling, and Quantization l Image Enhancement l Image Segmentation l Image Compression l Volumetric Image Analysis l Rendering Techniques

Learning Achievement

Getting acquainted with the fundamental image processing techniques for medical images

Competence

Course prerequisites

Grading Philosophy

Course schedule

Course type

Online Course Requirement

Instructor

Chung-Ming Chen

Other information

Graduate Institute of Biomedical Engineering

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