Spatially adapted augmentation of age-specific atlas-based segmentation using patch-based priors

Mengyuan Liu; Sharmishtaa Seshamani; Lisa Harrylock; Averi Kitsch; Steven Miller; Van Chau; Kenneth Poskitt; Francois Rousseau; Colin Studholme

doi:10.1117/12.2042426

21 March 2014 Spatially adapted augmentation of age-specific atlas-based segmentation using patch-based priors

Mengyuan Liu, Sharmishtaa Seshamani, Lisa Harrylock, Averi Kitsch, Steven Miller, Van Chau, Kenneth Poskitt, Francois Rousseau, Colin Studholme

Author Affiliations +

Proceedings Volume 9034, Medical Imaging 2014: Image Processing; 90341H (2014) https://doi.org/10.1117/12.2042426
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

One of the most common approaches to MRI brain tissue segmentation is to employ an atlas prior to initialize an Expectation- Maximization (EM) image labeling scheme using a statistical model of MRI intensities. This prior is commonly derived from a set of manually segmented training data from the population of interest. However, in cases where subject anatomy varies significantly from the prior anatomical average model (for example in the case where extreme developmental abnormalities or brain injuries occur), the prior tissue map does not provide adequate information about the observed MRI intensities to ensure the EM algorithm converges to an anatomically accurate labeling of the MRI. In this paper, we present a novel approach for automatic segmentation of such cases. This approach augments the atlas-based EM segmentation by exploring methods to build a hybrid tissue segmentation scheme that seeks to learn where an atlas prior fails (due to inadequate representation of anatomical variation in the statistical atlas) and utilize an alternative prior derived from a patch driven search of the atlas data. We describe a framework for incorporating this patch-based augmentation of EM (PBAEM) into a 4D age-specific atlas-based segmentation of developing brain anatomy. The proposed approach was evaluated on a set of MRI brain scans of premature neonates with ages ranging from 27.29 to 46.43 gestational weeks (GWs). Results indicated superior performance compared to the conventional atlas-based segmentation method, providing improved segmentation accuracy for gray matter, white matter, ventricles and sulcal CSF regions.

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Mengyuan Liu, Sharmishtaa Seshamani, Lisa Harrylock, Averi Kitsch, Steven Miller, Van Chau, Kenneth Poskitt, Francois Rousseau, and Colin Studholme "Spatially adapted augmentation of age-specific atlas-based segmentation using patch-based priors", Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90341H (21 March 2014); https://doi.org/10.1117/12.2042426

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