Automatic estimation of midline shift in patients with cerebral glioma based on enhanced voigt model and local symmetry

Australasian Physical & Engineering Sciences in Medicine
Mingyang ChenQingmao Hu

Abstract

Cerebral glioma is one of the most aggressive space-occupying diseases, which will exhibit midline shift (MLS) due to mass effect. MLS has been used as an important feature for evaluating the pathological severity and patients' survival possibility. Automatic quantification of MLS is challenging due to deformation, complex shape and complex grayscale distribution. An automatic method is proposed and validated to estimate MLS in patients with gliomas diagnosed using magnetic resonance imaging (MRI). The deformed midline is approximated by combining mechanical model and local symmetry. An enhanced Voigt model which takes into account the size and spatial information of lesion is devised to predict the deformed midline. A composite local symmetry combining local intensity symmetry and local intensity gradient symmetry is proposed to refine the predicted midline within a local window whose size is determined according to the pinhole camera model. To enhance the MLS accuracy, the axial slice with maximum MSL from each volumetric data has been interpolated from a spatial resolution of 1 mm to 0.33 mm. The proposed method has been validated on 30 publicly available clinical head MRI scans presenting with MLS. It delineates the deforme...Continue Reading

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Citations

Jan 17, 2019·Journal of Neurotrauma·Saurabh JainJan Verheyden
Jun 1, 2018·International Journal of Biomedical Imaging·Chun-Chih LiaoFuren Xiao
Dec 15, 2020·Journal of Neuroscience Methods·Manas Kumar NagNirmalya Ghosh
May 18, 2021·Frontiers in Aging Neuroscience·Adam GibicarApril Khademi

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