Brain tissue segmentation of neonatal MR images using a longitudinal subject-specific probabilistic atlas

Feng Shi; Yong Fan; Songyuan Tang; John Gilmore; Weili Lin; Dinggang Shen

doi:10.1117/12.811610

27 March 2009 Brain tissue segmentation of neonatal MR images using a longitudinal subject-specific probabilistic atlas

Feng Shi, Yong Fan, Songyuan Tang, John Gilmore, Weili Lin, Dinggang Shen

Proceedings Volume 7259, Medical Imaging 2009: Image Processing; 725942 (2009) https://doi.org/10.1117/12.811610
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Brain tissue segmentation of neonate MR images is a challenging task in study of early brain development, due to low signal contrast among brain tissues and high intensity variability especially in white matter. Among various brain tissue segmentation algorithms, the atlas-based segmentation techniques can potentially produce reasonable segmentation results on neonatal brain images. However, their performance on the population-based atlas is still limited due to the high variability of brain structures across different individuals. Moreover, it may be impossible to generate a reasonable probabilistic atlas for neonates without tissue segmentation samples. To overcome these limitations, we present a neonatal brain tissue segmentation method by taking advantage of the longitudinal data available in our study to establish a subject-specific probabilistic atlas. In particular, tissue segmentation of the neonatal brain is formulated as two iterative steps of bias correction and probabilistic atlas based tissue segmentation, along with the guidance of brain tissue segmentation resulted from the later time images of the same subject which serve as a subject-specific probabilistic atlas. The proposed method has been evaluated qualitatively through visual inspection and quantitatively by comparing with manual delineation results. Experimental results show that the utilization of a subject-specific probabilistic atlas can substantially improve tissue segmentation of neonatal brain images.

Citation Download Citation

Feng Shi, Yong Fan, Songyuan Tang, John Gilmore, Weili Lin, and Dinggang Shen "Brain tissue segmentation of neonatal MR images using a longitudinal subject-specific probabilistic atlas", Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 725942 (27 March 2009); https://doi.org/10.1117/12.811610

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