Interpolation of longitudinal shape and image data via optimal mass transport

Yi Gao; Liang-Jia Zhu; Sylvain Bouix; Allen Tannenbaum

doi:10.1117/12.2043282

21 March 2014 Interpolation of longitudinal shape and image data via optimal mass transport

Yi Gao, Liang-Jia Zhu, Sylvain Bouix, Allen Tannenbaum

Proceedings Volume 9034, Medical Imaging 2014: Image Processing; 90342X (2014) https://doi.org/10.1117/12.2043282
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

Longitudinal analysis of medical imaging data has become central to the study of many disorders. Unfortunately, various constraints (study design, patient availability, technological limitations) restrict the acquisition of data to only a few time points, limiting the study of continuous disease/treatment progression. Having the ability to produce a sensible time interpolation of the data can lead to improved analysis, such as intuitive visualizations of anatomical changes, or the creation of more samples to improve statistical analysis. In this work, we model interpolation of medical image data, in particular shape data, using the theory of optimal mass transport (OMT), which can construct a continuous transition from two time points while preserving “mass” (e.g., image intensity, shape volume) during the transition. The theory even allows a short extrapolation in time and may help predict short-term treatment impact or disease progression on anatomical structure. We apply the proposed method to the hippocampus-amygdala complex in schizophrenia, the heart in atrial fibrillation, and full head MR images in traumatic brain injury.

Citation Download Citation

Yi Gao, Liang-Jia Zhu, Sylvain Bouix, and Allen Tannenbaum "Interpolation of longitudinal shape and image data via optimal mass transport", Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90342X (21 March 2014); https://doi.org/10.1117/12.2043282

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