ENGG*4660 Medical Image Processing W (3-2) [0.50]
This course covers the fundamentals of medical image processing. Image processing topics covered include: fundamentals of resolution and quantization; linear systems as applied to multi-dimensional continuous and discrete systems; point operations such as contrast enhancement and histogram equalization; geometric operations for distortion correction, including interpolation methods; linear filtering in both the spatial and spatial-frequency domains; and image restoration and inverse filtering. Image segmentation is covered in the framework of pattern recognition using single and multiple dimensional features, and includes the fundamental Bayes classifier as well as machine learning methods for both supervised and unsupervised learning.
Prerequisite(s): ENGG*3390
Department(s): School of Engineering