Morphological Operators

I have taken a different approach to the pulmonary vein ostium search problem. 'Primitive' machine vision techniques such as opening and closing can be applied to certain binary images in order to decompose them into their meaningful parts and separate them from their extraneous parts. These happen to be very useful operators. It is derived from mathematical morphology which is a theoretical model for digital images built using lattice theory and topology. So it is back to the basics of machine vision - and I am a little more than glad that I am doing hands-on morphology. I take it as one of the 'must-know' concepts in machine vision.

I will be looking to separate the atrium from its pulmonary veins using these operators. Although surely the operators, on its own, will not be sufficient to do such a task. At this end, I am also looking to possibly implement knowledge-based operators. These operators will incorporate knowledge about the subdivisions (such as their radii, etc.)

Although reading about the fundamentals of mathematical morphology was not great fun, however, I found this book by Haralick to be really helpful. I also found these lecture notes from the U. of Edinburgh informatics site easy to read and understand.

This Friday I picked up more atrium data from my clinician. We are looking at the possibility of exploring a different technique to the atrium segmentation problem.