MENTOR: Prof. Gabor Fichtinger
Information:
www.cs.queensu.ca/~gabor, email: gabor@cs.queensu.ca
BACKGROUND AND SIGNIFICANCE
A significant problem in
planning of volumetrically prescribed localized treatments is the mathematical
impossibility to determine the exact 3D shape and volume of a target object
from a limited number of projected 2D X-ray images. Reconstruction accuracy
also varies with viewing angle, depending on the convexity and aspect ratios of
the target object. One of the especially difficult problems is planning the
radiosurgery of arterioveneous malformations (AVMs) that
present in the X-ray images as heap of vascular segments (pretty much like a
plate of spaghetti J)
PROJECT OBJECTIVES
You will develop a robust
and efficient technique for approximate volumetric reconstruction, which (A)
uses no prior information of the shape and volume of the target, (B) does not
require exact silhouettes, (C) accepts arbitrary number of images, (D) produces
solid object and measure of its volume, (E) provides confidence measure of the
reconstruction and drawing of silhouettes, (F) is robust, fast and easy to
implement.
SKILLS DEVELOPED
This project
concentrates on computing and takes you to a higher level of usage of some key
concepts and techniques learned in CISC-330. The project should ideally lead to new and publishable solution
and implementation of target reconstruction algorithm for stereotactic
intracranial radiosurgery.
BACKGROUND
REQUIRED
Programming
in MATLAB
Preferred:
having taken CISC-330 (Computer Integrated Surgery)