Boundary finding using Fourier surfaces of increasing order

Boundary finding in simulated medical images is performed by optimizing the Fourier coefficients in a parametric surface representation with respect to an objective function. The deformable model is fitted to the data using the brightness gradient component which is normal to the surface. A low order (<10) Fourier series expansion offers a sufficiently accurate representation for many inherently smooth objects that occur in medical imaging. Experimental results are presented for simulated image objects corresponding to organs of the anthropomorphic Zubal phantom. Two different optimization methods are studied concerning robustness and computational efficiency. The effect of increasing the Fourier expansion order is investigated for various noise levels (Less)