Contour-Driven Atlas-Based Segmentation
Name
Contour-driven.pdf
Size
2.81 MB
Format
Adobe PDF
Checksum (MD5)
de27b3f237afb7bc517f9ac64dc7bb2b
Author(s)
Wachinger, Christian
Fritscher, Karl
Sharp, Greg
Golland, Polina
Date Issued
December 2015
Journal
IEEE Transactions on Medical Imaging
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Wachinger, Christian et al. “Contour-Driven Atlas-Based Segmentation.” IEEE Transactions on Medical Imaging 34, 12 (December 2015): 2492–2505 © 2015 Institute of Electrical and Electronics Engineers (IEEE)
Version
Author's final manuscript
Abstract
We propose new methods for automatic segmentation of images based on an atlas of manually labeled scans and contours in the image. First, we introduce a Bayesian framework for creating initial label maps from manually annotated training images. Within this framework, we model various registration- and patch-based segmentation techniques by changing the deformation field prior. Second, we perform contour-driven regression on the created label maps to refine the segmentation. Image contours and image parcellations give rise to non-stationary kernel functions that model the relationship between image locations. Setting the kernel to the covariance function in a Gaussian process establishes a distribution over label maps supported by image structures. Maximum a posteriori estimation of the distribution over label maps conditioned on the outcome of the atlas-based segmentation yields the refined segmentation. We evaluate the segmentation in two clinical applications: the segmentation of parotid glands in head and neck CT scans and the segmentation of the left atrium in cardiac MR angiography images.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/TMI.2015.2442753
