A Stochastic Modeling Approach to 3-D Image Modeling

Dhiraj Joshi, Jia Li, James Z. Wang
The Pennsylvania State University

Statistical modeling methods have been successfully used to segment, classify, and annotate digital images, over the years. In this paper, we present a 3-D hidden Markov model (HMM) for volume image modeling. The 3-D HMMis applied to volume image segmentation and tested using synthetic images with ground truth. Potential applications to 3-D biomedical image analysis are also discussed.

Full Paper in Color
(PDF, 0.16MB)

More Info

Citation: Dhiraj Joshi, Jia Li and James Z. Wang, ``A Stochastic Modeling Approach to 3-D Image Modeling,'' Proceedings of the IEEE/NLM Life Science Systems and Application Workshop, pp. 120-121, IEEE, Bethesda, MD, July 2006.

Copyright 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the IEEE. Contact: Manager, Copyrights and Permissions / IEEE Service Center / 445 Hoes Lane / P.O. Box 1331 / Piscataway, NJ 08855-1331, USA. Telephone: + Intl. 732-562-3966.

Last Modified: June 28, 2006