COSC 6391 / COSC 4397
Biomedical Image Analysis

http://www.cbl.uh.edu/~6391f06

Fall 2006

OVERVIEW

Have you ever wondered what role images can play in Medicine and Biology?

What can a computer scientist do with images?

Would you like a sneak peek into the future of Preemptive-Predictive-Personalized Medicine?

This course is focusing on principles and computational methods for processing and analysis of biomedical images. Imaging refers to sensor instrumental generating multidimensional information on various levels of detail, contrast, temporal, and spectral resolution. In image analysis, the focus is on algorithms that can be used to interpret an image in terms of content and properties (e.g., what are their characteristics (size, shape, texture, color, motion) of objects in the image). The link between theoretical fundamentals, advanced algorithms, and real-life applications will be accomplished through hands-on exercises and projects.

TOPICS

• Biomedical image processing: spatial, frequency-domain, and morphological filtering
• Biomedical image segmentation: clustering, deformable models, region-based, and level-set approaches
• Biomedical image registration: spatial transformations, similarity metrics, image interpolation, and optimization
• Shape/Motion Modeling and Estimation: statistics- and physics-based models
• Validation in Biomedical Image Analysis
• Software Tools: ITK, MATLAB, and VOLVIEW

PREREQUISITES

Programming knowledge and experience in C++.

EVALUATION

TEXTBOOK

(IPAMV) - M. Sonka, V. Hlavac, and R. Boyle, Image Processing, Analysis, and Machine Vision, 2nd Edition, Brooks/Cole, 1999

REFERENCES

(HMI) - M. Sonka and J. Beutel, Handbook of Medical Imaging

(IIM) - T. Yoo, Insight into Images

INSTRUCTOR

Professor Ioannis A. Kakadiaris
Department of Computer Science, University of Houston
209 Philip G. Hoffman (PGH) Hall
Tel: (713) 743-1255
Email: ioannisk@uh.edu
URL: http://www.cbl.uh.edu/~ioannisk