Exploiting self-similarity of arterial trees to reduce the complexity of analysis

Roger H. Johnson; Kelly L. Karau; Robert C. Molthen; Christopher A. Dawson

doi:10.1117/12.349605

20 May 1999 Exploiting self-similarity of arterial trees to reduce the complexity of analysis

Roger H. Johnson, Kelly L. Karau, Robert C. Molthen, Christopher A. Dawson

Proceedings Volume 3660, Medical Imaging 1999: Physiology and Function from Multidimensional Images; (1999) https://doi.org/10.1117/12.349605
Event: Medical Imaging '99, 1999, San Diego, CA, United States

Abstract

Vascular structures such as the pulmonary arterial tree contain hundreds of thousands of vessel segments, making structural and functional analysis of an entire 3D image volume very difficult. Currently-available methods for segmentation and morphometry of 3D vascular tree images require user interaction making the task very tedious and sometimes impossible. Our aim is to exploit the self-similar nature of arterial trees to simplify morphometric analysis. The structure of pulmonary arterial trees exhibits self- similarity in the sense that the segment length and diameter data from different pathways are statistically indistinguishable for subtrees distal to a given segment diameter. We analyze 3D micro-CT images of mouse and rat pulmonary arterial trees by measuring the lengths and diameters of the vessel segments of the several longest arterial pathways and their immediate branches interactively. Since measurements made on the longest pathways are representative of the tree as a whole, and there are less than 30 branches off the main trunk, the morphometry of the complex tree can be characterized by less than 100 length and diameter measurements.

Citation Download Citation

Roger H. Johnson, Kelly L. Karau, Robert C. Molthen, and Christopher A. Dawson "Exploiting self-similarity of arterial trees to reduce the complexity of analysis", Proc. SPIE 3660, Medical Imaging 1999: Physiology and Function from Multidimensional Images, (20 May 1999); https://doi.org/10.1117/12.349605

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