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Automatic Brain Extraction for Rodent MRI Images

机译：啮齿动物MRI图像的自动脑提取

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摘要

Rodent models are increasingly important in translational neuroimaging research. In rodent neuroimaging, particularly magnetic resonance imaging (MRI) studies, brain extraction is a critical data preprocessing component. Current brain extraction methods for rodent MRI usually require manual adjustment of input parameters due to widely different image qualities and/or contrasts. Here we propose a novel method, termed SHape descriptor selected Extremal Regions after Morphologically filtering (SHERM), which only requires a brain template mask as the input and is capable of automatically and reliably extracting the brain tissue in both rat and mouse MRI images. The method identifies a set of brain mask candidates, extracted from MRI images morphologically opened and closed sequentially with multiple kernel sizes, that match the shape of the brain template. These brain mask candidates are then merged to generate the brain mask. This method, along with four other state-of-the-art rodent brain extraction methods, were benchmarked on four separate datasets including both rat and mouse MRI images. Without involving any parameter tuning, our method performed comparably to the other four methods on all datasets, and its performance was robust with stably high true positive rates and low false positive rates. Taken together, this study provides a reliable automatic brain extraction method that can contribute to the establishment of automatic pipelines for rodent neuroimaging data analysis.
机译：啮齿动物模型在翻译神经影像学研究中越来越重要。在啮齿动物的神经影像动物中，特别是磁共振成像（MRI）研究，脑提取是关键数据预处理组分。由于图像质量广泛和/或对比，目前靶脑提取方法通常需要手动调整输入参数。在这里，我们提出了一种新的方法，所述形状描述符在形态学过滤（Shrm）之后选择的极端区域，其仅需要脑模板掩模作为输入，并且能够自动且可靠地在大鼠和小鼠MRI图像中提取脑组织。该方法识别一组脑掩模候选者，从MRI图像中提取，与多个核尺寸顺序地，与脑模板的形状依次依次打开和闭合。然后将这些脑面膜候选人合并以产生脑面膜。这种方法以及其他四种最先进的啮齿动物脑提取方法在四个单独的数据集上基准测试，包括大鼠和小鼠MRI图像。在不涉及任何参数调谐的情况下，我们的方法与所有数据集的其他四种方法相当执行，其性能具有稳定的真实阳性率和低误率的稳定性。这项研究总结在一起，提供可靠的自动脑提取方法，可以有助于建立用于啮齿动物神经影像数据分析的自动管道。

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