-
Notifications
You must be signed in to change notification settings - Fork 5
Home
Welcome to the Chaotic Sensing (ChaoS) wiki!
In these series of pages, we will try and cover the many aspects of ChaoS that make it tick. These include how discrete Radon transforms (DRT) work, what the finite maximum likelihood expectation maximization (fMLEM) does and how fractals make it all happen.
We will also summarise the different important works related to ChaoS as a supplement to our IEEE Trans. on Imag. Proc. paper. See the slides of the work recently presented by Dr. Chandra at UQ.
The main components of ChaoS are the following:
- Discrete Radon transform (DRT) and its resulting discrete Fourier slice theorem (FST)
- Chaotic mixing of image information
- Finite iterative reconstruction
The pattern and its process are akin to trying to see the reflection of your face in the surface of a pond. When we measure completely, without trying to be efficient or smart and ensuring we get all the information possible, it is if there is no disturbance in the pond and your face is easy to see. However, the conditions must be perfect and, in terms of MRI, it takes a long time to acquire all these measurements, but the image of the organ/tissue is straight forward to obtain.
The fractal nature of the pattern is important because when we discard or have missing measurements, it is as if the surface of the pond is no longer still. In fact, the pond surface becomes disturbed with many, many ripples that is usually no way to resolving or reconciling a face on the surface anymore. What the fractal nature of the pattern allows us to do is to ensure that these ripples interact with each other in such a precise way that they all cancel each other out, so that we can see our face once again. The cancelling out of these artefacts is done by producing turbulence among the ripples and amounts to a chaotic mixing of image information, which is why the work is called Chaotic Sensing.
Detailed explanations of discrete transforms found in Chandra's thesis: http://arrow.monash.edu.au/hdl/1959.1/289983