Robust midsagittal plane extraction from normal and pathological 3-D neuroradiology images

Yanxi Liu, Robert Collins, William E. Rothfus

Research output: Contribution to journalArticle

114 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)175-192
Number of pages18
JournalIEEE Transactions on Medical Imaging
Volume20
Issue number3
DOIs
StatePublished - Mar 1 2001

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Three-Dimensional Imaging
Brain
Signal-To-Noise Ratio
Signal to noise ratio

All Science Journal Classification (ASJC) codes

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

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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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Robust midsagittal plane extraction from normal and pathological 3-D neuroradiology images. / Liu, Yanxi; Collins, Robert; Rothfus, William E.

In: IEEE Transactions on Medical Imaging, Vol. 20, No. 3, 01.03.2001, p. 175-192.

Research output: Contribution to journalArticle

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