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

机译:脑中线偏移测量及其自动化:技术和算法的回顾

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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:大脑的中线移位(MLS)是一项重要功能,可以使用各种成像方式进行测量,包括X射线,超声,计算机断层扫描和磁共振成像。中线颅内结构的移位有助于诊断颅内病变,尤其是颅脑外伤,中风,脑瘤和脓肿。作为颅内压升高的标志,MLS也是颅内质量或质量效应引起的脑灌注减少的指标。我们回顾了使用MLS预测颅内肿块患者预后的研究。在某些研究中,MLS也与临床特征相关。自动化的MLS测量算法具有巨大的潜力,可协助人类专家评估大脑图像。在基于对称的算法中,检测到变形的中线,并将其与理想中线的距离作为MLS。在基于地标的地标中,在确定特定解剖学地标之后测量了MLS。为了验证这些算法,将使用这些算法的测量值与人类专家进行的MLS测量值进行了比较。除了在给定的影像学研究中测量MLS之外,MLS还有一些新的应用,包括比较治疗前后的多次MLS测量以及开发额外的功能以指示质量效应。提供了未来研究的建议。

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