Return to search

A Unified Statistical and Information Theoretic Framework for Multi-modal Image Registration

We formulate and interpret several multi-modal registration methods in the context of a unified statistical and information theoretic framework. A unified interpretation clarifies the implicit assumptions of each method yielding a better understanding of their relative strengths and weaknesses. Additionally, we discuss a generative statistical model from which we derive a novel analysis tool, the "auto-information function", as a means of assessing and exploiting the common spatial dependencies inherent in multi-modal imagery. We analytically derive useful properties of the "auto-information" as well as verify them empirically on multi-modal imagery. Among the useful aspects of the "auto-information function" is that it can be computed from imaging modalities independently and it allows one to decompose the search space of registration problems.

Identiferoai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/6738
Date28 April 2004
CreatorsZollei, Lilla, Fisher, John, Wells, William
Source SetsM.I.T. Theses and Dissertation
Languageen_US
Detected LanguageEnglish
Format21 p., 2760680 bytes, 531001 bytes, application/postscript, application/pdf
RelationAIM-2004-011

Page generated in 0.0015 seconds