Fast correspondences search in anatomical trees

Thiago R. dos Santos; Ingmar Gergel; Hans-Peter Meinzer; Lena Maier-Hein

doi:10.1117/12.844192

12 March 2010 Fast correspondences search in anatomical trees

Thiago R. dos Santos, Ingmar Gergel, Hans-Peter Meinzer, Lena Maier-Hein

Proceedings Volume 7623, Medical Imaging 2010: Image Processing; 762332 (2010) https://doi.org/10.1117/12.844192
Event: SPIE Medical Imaging, 2010, San Diego, California, United States

Abstract

Registration of multiple medical images commonly comprises the steps feature extraction, correspondences search and transformation computation. In this paper, we present a new method for a fast and pose independent search of correspondences using as features anatomical trees such as the bronchial system in the lungs or the vessel system in the liver. Our approach scores the similarities between the trees' nodes (bifurcations) taking into account both, topological properties extracted from their graph representations and anatomical properties extracted from the trees themselves. The node assignment maximizes the global similarity (sum of the scores of each pair of assigned nodes), assuring that the matches are distributed throughout the trees. Furthermore, the proposed method is able to deal with distortions in the data, such as noise, motion, artifacts, and problems associated with the extraction method, such as missing or false branches. According to an evaluation on swine lung data sets, the method requires less than one second on average to compute the matching and yields a high rate of correct matches compared to state of the art work.

Citation Download Citation

Thiago R. dos Santos, Ingmar Gergel, Hans-Peter Meinzer, and Lena Maier-Hein "Fast correspondences search in anatomical trees", Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 762332 (12 March 2010); https://doi.org/10.1117/12.844192

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