Robust midsagittal plane extraction from normal and pathological 3-D neuroradiology images
Yanxi Liu
Collins, R.T.
Rothfus, W.E.
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA;
This paper appears in: Medical Imaging, IEEE Transactions on
Publication Date: March 2001
Volume: 20,
Issue: 3
On page(s): 175-192
Location: Davis, CA, USA,
ISSN: 0278-0062
References Cited: 35
CODEN: ITMID4
INSPEC Accession Number: 6925714
Digital Object Identifier: 10.1109/42.918469
Current Version Published: 2002-08-07
Abstract
This paper focuses on extracting the ideal midsagittal plane (iMSP) from three-dimensional (3-D) normal and pathological neuroimages. The main challenges in this work are the structural asymmetry that may exist in pathological brains, and the anisotropic, unevenly sampled image data that is common in clinical practice. We present an edge-based, cross-correlation approach that decomposes the plane fitting problem into discovery of two-dimensional symmetry axes on each slice, followed by a robust estimation of plane parameters. The algorithm's tolerance to brain asymmetries, input image offsets and image noise is quantitatively evaluated. We find that the algorithm can extract the iMSP from input 3-D images with 1) large asymmetrical lesions; 2) arbitrary initial rotation offsets; 3) low signal-to-noise ratio or high bias field. The iMSP algorithm is compared with an approach based on maximization of mutual information registration, and is found to exhibit superior performance under adverse conditions. Finally, no statistically significant difference is found between the midsagittal plane computed by the iMSP algorithm and that estimated by two trained neuroradiologists.
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