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Unsupervised Pathological Area Extraction using 3D T2 and FLAIR MR Images

机译：使用3D T2和FLAIR MR图像的无监督病理区域提取

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This work discusses fully automated extraction of brain tumor and edema in 3D MR volumes. The goal of this work is the extraction of the whole pathological area using such an algorithm that does not require a human intervention. For the good visibility of these kinds of tissues both T2-weighted and FLAIR images were used. The proposed method was tested on 80 MR volumes of publicly available BRATS database, which contains high and low grade gliomas, both real and simulated. The performance was evaluated by the Dice coefficient, where the results were differentiated between high and low grade and real and simulated gliomas. The method reached promising results for all of the combinations of images: real high grade (0.73 ± 0.20), real low grade (0.81 ± 0.06), simulated high grade (0.81 ± 0.14), and simulated low grade (0.81 ± 0.04).
机译：这项工作讨论了3D MR体积中脑肿瘤和水肿的全自动提取。这项工作的目标是使用不需要人工干预的算法提取整个病理区域。为了使这类组织具有良好的可见性，使用了T2加权图像和FLAIR图像。该方法在80 MR的公开BRATS数据库中进行了测试，该数据库包含真实和模拟的高等级和低等级神经胶质瘤。通过Dice系数对性能进行评估，在该结果中，结果分为高低等级，真实和模拟神经胶质瘤。该方法在所有图像组合上均取得了令人满意的结果：真实高等级（0.73±0.20），真实低等级（0.81±0.06），模拟高等级（0.81±0.14）和模拟低等级（0.81±0.04）。

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