In this article we will present Point Distribution Models (PDMs) constructe
d from Magnetic Resonance scanned foetal livers and will investigate their
use in reconstructing 3D shapes from sparse data, as an aid to volume estim
ation. A solution of the model to data matching problem will be presented t
hat is based on a hybrid Genetic Algorithm (GA). The GA has amongst its gen
etic operators, elements that extend the general Iterative Closest Point (I
CP) algorithm to include deformable shape parameters. Results from using th
e GA to estimate volumes from two sparse sampling schemes will be presented
. We will show how the algorithm can estimate liver volumes in the range of
10.26 to 28.84 cc with an accuracy of 0.17 +/- 4.44% when using only three
sections through the liver volume. (C) 1999 Published by Elsevier Science
B.V. All rights reserved.