Brain Midline Shift Measurement and Its Automation: A Review of Techniques and Algorithms
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 resonance imaging. Shift of midline intracranial structures helps diagnosing intracranial lesions, especially traumatic brain...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2018/4303161 |
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| _version_ | 1832557066709893120 |
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| author | Chun-Chih Liao Ya-Fang Chen Furen Xiao |
| author_facet | Chun-Chih Liao Ya-Fang Chen Furen Xiao |
| author_sort | Chun-Chih Liao |
| collection | DOAJ |
| description | 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 resonance imaging. Shift of midline intracranial structures helps diagnosing intracranial lesions, especially traumatic brain injury, stroke, brain tumor, and abscess. Being a sign of increased intracranial pressure, MLS is also an indicator of reduced brain perfusion caused by an intracranial mass or mass effect. We review studies that used the MLS to predict outcomes of patients with intracranial mass. In some studies, the MLS was also correlated to clinical features. Automated MLS measurement algorithms have significant potentials for assisting human experts in evaluating brain images. In symmetry-based algorithms, the deformed midline is detected and its distance from the ideal midline taken as the MLS. In landmark-based ones, MLS was measured following identification of specific anatomical landmarks. To validate these algorithms, measurements using these algorithms were compared to MLS measurements made by human experts. In addition to measuring the MLS on a given imaging study, there were newer applications of MLS that included comparing multiple MLS measurement before and after treatment and developing additional features to indicate mass effect. Suggestions for future research are provided. |
| format | Article |
| id | doaj-art-ede35d511e4f437493301c998cdbcf2d |
| institution | Kabale University |
| issn | 1687-4188 1687-4196 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Biomedical Imaging |
| spelling | doaj-art-ede35d511e4f437493301c998cdbcf2d2025-02-03T05:43:43ZengWileyInternational Journal of Biomedical Imaging1687-41881687-41962018-01-01201810.1155/2018/43031614303161Brain Midline Shift Measurement and Its Automation: A Review of Techniques and AlgorithmsChun-Chih Liao0Ya-Fang Chen1Furen Xiao2Institute of Biomedical Engineering, National Taiwan University, No. 1, Sec. 1, Renai Rd., Taipei City 10051, TaiwanDepartment of Medical Imaging, National Taiwan University Hospital, No. 7, Zhongshan S. Rd., Taipei City 10002, TaiwanInstitute of Biomedical Engineering, National Taiwan University, No. 1, Sec. 1, Renai Rd., Taipei City 10051, TaiwanMidline 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 resonance imaging. Shift of midline intracranial structures helps diagnosing intracranial lesions, especially traumatic brain injury, stroke, brain tumor, and abscess. Being a sign of increased intracranial pressure, MLS is also an indicator of reduced brain perfusion caused by an intracranial mass or mass effect. We review studies that used the MLS to predict outcomes of patients with intracranial mass. In some studies, the MLS was also correlated to clinical features. Automated MLS measurement algorithms have significant potentials for assisting human experts in evaluating brain images. In symmetry-based algorithms, the deformed midline is detected and its distance from the ideal midline taken as the MLS. In landmark-based ones, MLS was measured following identification of specific anatomical landmarks. To validate these algorithms, measurements using these algorithms were compared to MLS measurements made by human experts. In addition to measuring the MLS on a given imaging study, there were newer applications of MLS that included comparing multiple MLS measurement before and after treatment and developing additional features to indicate mass effect. Suggestions for future research are provided.http://dx.doi.org/10.1155/2018/4303161 |
| spellingShingle | Chun-Chih Liao Ya-Fang Chen Furen Xiao Brain Midline Shift Measurement and Its Automation: A Review of Techniques and Algorithms International Journal of Biomedical Imaging |
| title | Brain Midline Shift Measurement and Its Automation: A Review of Techniques and Algorithms |
| title_full | Brain Midline Shift Measurement and Its Automation: A Review of Techniques and Algorithms |
| title_fullStr | Brain Midline Shift Measurement and Its Automation: A Review of Techniques and Algorithms |
| title_full_unstemmed | Brain Midline Shift Measurement and Its Automation: A Review of Techniques and Algorithms |
| title_short | Brain Midline Shift Measurement and Its Automation: A Review of Techniques and Algorithms |
| title_sort | brain midline shift measurement and its automation a review of techniques and algorithms |
| url | http://dx.doi.org/10.1155/2018/4303161 |
| work_keys_str_mv | AT chunchihliao brainmidlineshiftmeasurementanditsautomationareviewoftechniquesandalgorithms AT yafangchen brainmidlineshiftmeasurementanditsautomationareviewoftechniquesandalgorithms AT furenxiao brainmidlineshiftmeasurementanditsautomationareviewoftechniquesandalgorithms |