Medical Physics Research Today is a free monthly online journal that collates and summarizes the latest research about Medical Physics, including details on medicine, radiotherapy, biomechanics, medical imaging.

Automatic seed initialization for the expectation-maximization algorithm and its application in 3D medical imaging.

Lynch M, Ilea D, Robinson K, Ghita O, Whelan PF

Vision Systems Group, Dublin City University, Dublin 9, Ireland.

Statistical partitioning of images into meaningful areas is the goal of all region-based segmentation algorithms. The clustering or creation of these meaningful partitions can be achieved in number of ways but in most cases it is achieved through the minimization or maximization of some function of the image intensity properties. Commonly these optimization schemes are locally convergent, therefore initialization of the parameters of the function plays a very important role in the final solution. In this paper we perform an automatically initialized expectation-maximization algorithm to partition the data in medical MRI images. We present analysis and illustrate results against manual initialization and apply the algorithm to some common medical image processing tasks.

Published 16 August 2007 in J Med Eng Technol, 31(5): 332-40.
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