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Brain Midline Shift Measurement and Its Automation: A Review of Techniques and Algorithms

机译:脑中线移位测量及其自动化:技术与算法综述

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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.
机译:大脑中线移位(MLS)是可以使用包括X射线,超声波,计算机断层扫描和磁共振成像的各种成像模码来测量的重要特征。中线颅内结构的转变有助于诊断颅内病变,尤其是创伤性脑损伤,中风,脑肿瘤和脓肿。作为颅内压的迹象,MLS也是由颅内质量或质量效应引起的减少脑灌注的指标。我们审查使用MLS预测颅内质量患者的结果的研究。在一些研究中,MLS也与临床特征相关。自动MLS测量算法具有辅助人类专家评估脑图像的潜力。在基于对称性的算法中,检测到变形的中线,其距离理想中线作为MLS的距离。在基于地标的基础上,在识别特定解剖标记之后测量MLS。为了验证这些算法,将使用这些算法的测量与人类专家进行的MLS测量进行比较。除了测量给定的成像研究的MLS之外,MLS还具有更新的MLS,包括比较治疗前后多种MLS测量并开发额外的特征来表示质量效应。提供了未来研究的建议。

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