Tuesday, January 11th, 2011, 10:23 am
Heart Tracking With Fusion of Edge Detection Maps
Filed under: 
currently put the final touches on my program which detects and analyses the movement of the heart using the fiesta protocol in an MRI-type modality (1.5 Tesla).
Recent and very simplistic experiments, where two rather distinct images were taken from the set and then rotated, were used such that the only real and anatomical shift is a rigid, geometric one. Two sorts of transformations were used; firstly, in two cases the images were rotated about the middle and in one case the rotation was around one of the corners. This gave different types of variations and various parameters were changes until the algorithm was able to track the points (placed at the edges) rather well. There are now new parameters in place, e.g. (in this case):
threshold = 1 transform_type = sum frame_size = 2 shuffle_radius = 1 draw_grid = 0 arrow_type = gradient verbosity = 1 output_type = image draw_circles = 1 triagulate = 1 measure_tangent_component = 1 search_along_gradient = 1 gradient_search_range = 2 boundaries_line_width = 2 ...
Going under the suffix “mid” (slice 3 from the bottom) we have an example of how the landmark points get moved between the frames.
Initial frame
Initial frame with landmark points on
Initial frame with connected landmark points
Position of landmark points at the end of the tracking sequence
Looking at edge detectors we have the possibility of fusion for improved tracking — with a two-tier image, one for the derivative and another being the original.
Sample image
Sobel edge detection of the image
Prewitt edge detection of the image
As an engine, I am currently using MATLAB for reasons of succession (other users of the program I built are less likely to run it in Octave like I do), but I don’t touch the MATLAB ‘desktop’, just the bash shell and vi as the editor (ncurses).
