Re-embedding vs. clustering as shape indexing strategies for medical image databases

Xiaoning Qian; Hemant D. Tagare; Robert K. Fulbright

doi:10.1117/12.595280

15 April 2005 Re-embedding vs. clustering as shape indexing strategies for medical image databases

Xiaoning Qian, Hemant D. Tagare, Robert K. Fulbright

Proceedings Volume 5748, Medical Imaging 2005: PACS and Imaging Informatics; (2005) https://doi.org/10.1117/12.595280
Event: Medical Imaging, 2005, San Diego, California, United States

Abstract

Fast retrieval using complete or partial shapes of organs is an important functionality in medical image databases. Shapes of organs can be defined as points in shape spaces, which, in turn, are curved manifolds with a well-defined metric. In this paper, we experimentally compare two indexing techniques for shape spaces: first, we re-embed the shape space in a Euclidean space and use co-ordinate based indexing, and second, we used metric based hierarchical clustering for directly indexing shape space. The relative performances are evaluated with images from the NHANES II database of lumbar and cervical spine x-ray images on a shape similarity query. The experiments show that indexing using re-embedding is superior to cluster-based indexing.

Citation Download Citation

Xiaoning Qian, Hemant D. Tagare, and Robert K. Fulbright "Re-embedding vs. clustering as shape indexing strategies for medical image databases", Proc. SPIE 5748, Medical Imaging 2005: PACS and Imaging Informatics, (15 April 2005); https://doi.org/10.1117/12.595280

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