Brain midline shift measurement and its automation: a review of techniques and algorithms

CC Liao, YF Chen, F Xiao - International journal of biomedical …, 2018 - Wiley Online Library
Midline shift (MLS) of the brain is an important feature that can be measured using various
imaging modalities including X‐ray, ultrasound, computed tomography, and magnetic …

Automatic quantification of computed tomography features in acute traumatic brain injury

S Jain, TV Vyvere, V Terzopoulos, DM Sima… - Journal of …, 2019 - liebertpub.com
Traumatic brain injury is a complex and diverse medical condition with a high frequency of
intracranial abnormalities. These can typically be visualized on a computed tomography …

Automatic symmetry detection from brain MRI based on a 2-channel convolutional neural network

H Wu, X Chen, P Li, Z Wen - IEEE Transactions on Cybernetics, 2019 - ieeexplore.ieee.org
Symmetry detection is a method to extract the ideal mid-sagittal plane (MSP) from brain
magnetic resonance (MR) images, which can significantly improve the diagnostic accuracy …

Brain midline shift detection and quantification by a cascaded deep network pipeline on non-contrast computed tomography scans

NP Nguyen, Y Yoo, A Chekkoury… - Proceedings of the …, 2021 - openaccess.thecvf.com
Brain midline shift (MLS), demonstrated by imaging, is a qualitative and quantitative
radiological feature which measures the extent of lateral shift of brain midline structures in …

An accurate skin lesion classification using fused pigmented deep feature extraction method

R Javed, M Shafry Mohd Rahim, T Saba… - Prognostic Models in …, 2022 - Springer
Melanoma is one of the riskiest diseases that extensively influence the quality of life and can
be dangerous or even fatal. Skin lesion classification methods faced challenges in varying …

Quantitative analysis of brain herniation from non-contrast CT images using deep learning

MK Nag, A Gupta, AS Hariharasudhan… - Journal of Neuroscience …, 2021 - Elsevier
Background Brain herniation is one of the fatal outcomes of increased intracranial pressure
(ICP). It is caused due to the presence of hematoma or tumor mass in the brain. Ideal midline …

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

M Chen, A Elazab, F Jia, J Wu, G Li, X Li… - Australasian physical & …, 2015 - Springer
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 …

[HTML][HTML] Automated detection of 3D midline shift in spontaneous supratentorial intracerebral haemorrhage with non-contrast computed tomography using deep …

X Xia, X Zhang, Z Huang, Q Ren, H Li, Y Li… - American Journal of …, 2021 - ncbi.nlm.nih.gov
Deep learning (DL)-based convolutional neural networks facilitate more accurate detection
and rapid analysis of MLS. Our objective was to assess the feasibility of applying a DL …

Automatic midline shift detection in traumatic brain injury

M Hooshmand, SMR Soroushmehr… - 2018 40th Annual …, 2018 - ieeexplore.ieee.org
Fast and accurate midline shift (MLS) estimation has a significant impact on diagnosis and
treatment of patients with Traumatic Brain Injury (TBI). In this paper, we propose an …

[HTML][HTML] Three dimensional convolutional neural network-based automated detection of midline shift in traumatic brain injury cases from head computed tomography …

D Agrawal, S Joshi, V Bahel… - … of Neurosciences in …, 2024 - ncbi.nlm.nih.gov
Objectives: Midline shift (MLS) is a critical indicator of the severity of brain trauma and is
even suggestive of changes in intracranial pressure. At present, radiologists have to …