Ganesh Swami

I’m taking just one course this semester — a special topics course on Computational Anatomy and Medical Image Analysis. The course is highly focused on the research interests of my supervisor, so instead of sitting beside each other in the lab, we go to another class room and sit beside each other.

Computational Anatomy is “the use of mathematical analysis to learn how tissues grow, assume new shapes and morph into mature structures.” The first few classes are review of the pre-requisites – linear systems theory and stochastic systems. Having not taken either of these courses, I’m seeing plenty of new material. A lot of it is intuitive, some of it not obvious at all. Overall a Good Thing.

I don’t have a copy of the outline yet, but some of the topics we are going to cover are vector space theory, variational calculus, differential and riemannian geometry, tensor analysis and applications in Computational Anatomy. An example of an application is what I’ve just finished writing — linear statistical analysis to classify the hippocampus in dementia of the Alzheimer’s type.

I’ll be posting about things that I find interesting here. If you’re in the class and want to follow along, a quick way to do so if by bookmarking the tag: ensc462.

Sometime last week, the members of the Medical Image Analysis Lab held an openhouse to attract new students. The idea was to showcase some of the work being done and I guess to see how this is relevant in the long run.

Download the full resolution of the handouts.

The aforementioned report is now ready for your immediate consumption. A single slide on my Fluid Match has been expanded to a whole section. Took me a little longer than I thought it would, but this is behind me now. I think I’ve more or less achieved what I set in front of me eight months back.

I could have talked about the implementation for a massively parallel supercomputer, but I was already pushing the page limits.

• Variational Inexact Image Matching

Keywords: optimization, variational, registration, diffeomorphisms, fluid-match, statistical tests, Alzheimer’s.

Still Alive. It’s been relatively quite here because I’ve been swamped with end-of-term activities. The problem with working on five year long projects is that deadlines are self-imposed. My strategy has been to make sticky notes with tasks and not getting up until I strike off the task and crumple the note. This has been super effective for me. It’s nice to feel a sense of accomplishment at the end of the day with the big pile of crumpled notes. Hey, what ever works!

This isn’t so good for learning stuff. I’ve had to do a fair bit of machine learning for some of the tasks I’m doing right now, and all of the language is foreign to me. It took me about a week to learn how to check for group mean differences between samples, but only about an hour to implement it in code. I guess this is “holding a program in one’s head.“

To meet accreditation requirements, Engineering students are required to do a major work term report atleast once. This is a big undertaking. Fortunately, I’m doing mine on my latest infatuation: fluid match. I’ve written a couple of sections, but it’s still lacking cohesiveness.

I’m also happy to say that I’ve decided to do my honors thesis at the Medical Image Analysis Lab, where I’ve been working for the past eight months. The exact details of my project are to worked out, so I don’t have much to say at this point.

I didn’t know what some of the settings on my camera were and this bothered me. I whipped out the manual (I thought I had trashed it, as I usually do) and checked it out. I can now take pictures like the one above with little difficulty, and it looks like I know what I’m doing. It’s still long ways before I exhaust the capabilities of my current camera.

Life’s Good.

Not for grocery, clothes, shoes, electronics or a car, but for university courses!

This made me laugh so much that it made me cry. Or maybe the other way.