1. Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology 1 f-information measures in medical image registration Presenter : Ai-Chen Liao Authors : Josien P.W. Pluim, J.B. Anotoine Maintz, and Max A. Viergever 2004. MI. Page : 1508 - 1516

2. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Medical Image Registration  Registration is necessary in order to be able to compare or integrate the data obtained from different measurements.  Image registration is the process of transforming the different sets of data into one coordinate system.  Medical image registration (e.g. for data of the same patient taken at different points in time)

3. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 3 Outline Motivation Objective Method Experiment Conclusion Comments

4. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 4 Motivation  In the mid 1990s, mutual information made its entrance into the field of medical image registration.  A measure for registration of medical images that currently draws much attention is mutual information.  Apart from mutual information, information theory comprises many more information measures, which could be considered for image registration. -information Whether is the optimal registration measure of the class of measures. What the influence of the order is on the registration results. mutual information

5. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 5 Objective  This paper compares the performance of mutual information as a registration measure with that of other -information measures.

6. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Method ─ -divergence  The extent to which two probability distributions differ can be expressed by a so-called measure of divergence.  A specific class of divergence measures is the set of measures.

7. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Method ─ -information  A special case of divergence are the information measures.

8. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Method ─ -information

9. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Method Mutual information

10. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 10 Experiment

11. Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiment

12. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 12 Conclusion  In this paper we compare mutual information with several other -information measures by applying them to the registration of clinical MR, PET, and CT images.  For the accuracy experiments, significantly better results were found for several measures, compared to mutual information.

13. Intelligent Database Systems Lab N.Y.U.S.T. I. M. 13 Comments Advantage  … Drawback  … Application  The field of medical image registration