This paper describes a technique for building compact models of the shape and appearance of flexible objects (such as organs) seen in 2D and 3D medical images. The models are derived from the statistics of sets of labelled images of examples of the objects. Each model consists of a flexible shape template, describing how important points of the objects can vary, and statistical models of the expected grey levels in regions around each model point. The shape models are parameterised in such a way as to allow only legal configurations. The models have proved useful in a wide variety of applications. We describe how they can be used in local image search and give examples of their application in medical image segmentation. We describe how 2D models can be used to segment 3D objects in volume images and to track structures in image sequences. We also describe how to generate full 3D models and illustrate their use to segment 3D Magnetic Resonance images of the brain.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 email@example.com
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 firstname.lastname@example.org