Automatic detection and quantification of brain midline shift using anatomical marker model

Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society
Ruizhe LiuCheng Kiang Lee

Abstract

Brain midline shift (MLS) is a significant factor in brain CT diagnosis. In this paper, we present a new method of automatically detecting and quantifying brain midline shift in traumatic injury brain CT images. The proposed method automatically picks out the CT slice on which midline shift can be observed most clearly and uses automatically detected anatomical markers to delineate the deformed midline and quantify the shift. For each anatomical marker, the detector generates five candidate points. Then the best candidate for each marker is selected based on the statistical distribution of features characterizing the spatial relationships among the markers. Experiments show that the proposed method outperforms previous methods, especially in the cases of large intra-cerebral hemorrhage and missing ventricles. A brain CT retrieval system is also developed based on the brain midline shift quantification results.

References

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Citations

Jun 1, 2018·International Journal of Biomedical Imaging·Chun-Chih LiaoFuren Xiao
Sep 1, 2015·Australasian Physical & Engineering Sciences in Medicine·Mingyang ChenQingmao Hu
Dec 15, 2020·Journal of Neuroscience Methods·Manas Kumar NagNirmalya Ghosh
Jul 3, 2021·International Journal of Environmental Research and Public Health·Vidhya VU Rajendra Acharya

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brain injury after impact to the head is due to both immediate mechanical effects and delayed responses of neural tissues.

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