Feature-based technique for automated image registration of the brain

Li-Yueh Hsu; Murray H. Loew

doi:10.1117/12.384878

5 May 2000 Feature-based technique for automated image registration of the brain

Li-Yueh Hsu, Murray H. Loew

Proceedings Volume 3905, 28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making; (2000) https://doi.org/10.1117/12.384878
Event: 28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making, 1999, Washington, DC, United States

Abstract

In this paper, we present an automated multi-modality registration algorithm based on hierarchical feature extraction. The approach, which has not ben used previously, can be divided into two distinct stages: feature extraction and geometric matching. Two kinds of corresponding features - edge and surface - are extracted hierarchically from various image modalities. The registration then is performed using least-squares matching of the automatically extracted features. Both the robustness and accuracy of feature extraction and geometric marching steps are evaluated using simulated and patient images. The preliminary results show the error is on the average of one voxel. We have shown the proposed 3D registration algorithm provides a simple and fast method for automatic registering of MR-to-CT and MR-to- PET image modalities. Our results are comparable to other techniques and require no user interaction.

Citation Download Citation

Li-Yueh Hsu and Murray H. Loew "Feature-based technique for automated image registration of the brain", Proc. SPIE 3905, 28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making, (5 May 2000); https://doi.org/10.1117/12.384878

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available