Courses

Course Name: BME188 – Imaging Practicum

Institution: Dept of Biomedical Engineering, University of Iowa

Lecturer: Dr. Ge Wang

Description: The goal is to guide you through a complete research process and solve a real-world problem in medical imaging and image analysis. You may team up in pairs or work by themselves. Under supervision of the Instructor, you will either select a project from a list the instructor provides or propose one of their interests. Your project will involve either development or application of hardware and/or software. The work consists of the four components: literature review, proposal writing, execution of the research plan, preparation of a scientific publication.

Prerequisites: BME185 Physics and Analysis of Biomedical Images I, BME186 Physics and Analysis of Biomedical Images II

Course Name: Digital Picture Processing

Institution: Graduate School of Academia Sinica, Beijing, China

Lecturer: Dr. Ge Wang

Description: This course covers basic concepts, representative algorithms, and typical applications. Fourteen chapters: Introduction, Mathematical preliminaries, Visual perception, Digitization, Compression, Enhancement, Restoration, Reconstruction, Matching, Segmentation, Representation, Description; Digital picture processing systems; Major trends and literature searching.

Prerequisites: Advanced linear algebra, stochastic processes, linear system theory, digital signal processing

Textbook: A. Rosenfeld and A. C. Kak, Digital picture processing. Academic Press, New York, 1982

Course Name: Computer Vision

Institution: Graduate School of Academia Sinica, Beijing, China

Lecturer: Dr. Ge Wang

Description: While image processing techniques map images to images, computer vision methods map images to descriptions. This course provides a basis for research and development in the computer vision area. Introduction: Viewing computer vision in the perspectives of computer science, bionics, and philosophy; Pre-processing: Recovering 3D shape from image stereo pair, shading, and texture; motion analysis; Segmentation: Boundary detection and region growing; Geometrical structures: 2D and 3D; Relational structures: Knowledge representation and use; Expert vision systems.

Prerequisites: Digital picture processing, artificial intelligence

Textbook: D. H. Ballard and C. M. Brown, Computer Vision. Prentice-Hall, Englewood Cliffs, New Jersey, 1982

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