Another Week
I finally got my computer account with the Faculty of Applied Science (FAS) system. Our lab doesn’t have pre-determined computers for its members. You can sit at whatever computer is available at that moment. Most computer resources are remotely accessible, so it doesn’t really matter in the end. My workstation of choice is a dual Xeon processor machine with three gigs of RAM. I’ve never seen programs (specially firefox) startup so instantaneously. It’s great.
I’m still familiarizing myself with some of the terms that get thrown around so frequently. There are a lot of posters on the walls around the lab — I’ve been talking to people about them. A major theme seems to be quantifying diseases with deformations in body parts – specially the brain. We are still long ways from letting a computer do diagnosis though.
This lab is truly a multi-disciplinary one. People around me are taking classes in physiology, machine learning, signal processing and general anatomy. And non-linear physics. Some of the sample projects I’ve looked at is quite demanding on multiple levels. Start from the acquisition process in the clinics for data to all the way down to representing tensors in your programs. I don’t fully understand the scope of the projects to pick one, so I’ll have to do some more background reading.
On Friday, we had a talk by Dr. John Aldrich from the radiology department at the Vancouver General Hospital. His talk was on optimizing Computed Tomography for clinical studies. CT accounts for more than 60% of the radiation dose to patients in the hospital setting. Studies have shown that the dosage variation for the same examination can vary upto a factor of ten, ie 1000%.
The first part of his talk was on the basics of CT. When a X-ray is
shot through the body, it undergoes dissipation. Sensors on the other
side of the body measure the resulting intensity of the wave. Using
this, we can compute the value of 
, the dissipation
constant. This is a function of the density of the material. This is
how we can differentiate bones from tissues.
He then went on to the latest-and-greatest of CT machines. He compared designs from Siemens and Toshiba and the difference in methodology. One is optimized for acquisition time while the other is optimized for higher resolution.
The second half of his talk was on optimizing CT examinations. As mentioned earlier, radiation can vary significantly between examinations. Radiation from CT machines can pose a significant cancer risk. What Dr. Aldrich has done is optimize the radiation dosage intensity as a function of noise levels. It’s enough to maintain radiation levels just above a certain noise threshold so that diagnosis is possible. Anything more is not necessary.