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Development of an Automated Extraction Method for Liver Tumors in Three-Dimensional Multiphase Multislice Images

机译:三维多相多层图像中肝肿瘤自动提取方法的开发

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This paper proposes an automatic method for extracting liver tumors from three-dimensional abdominal CT images of four phases (noncontrast, early phase, portal phase, late phase). In the proposed method, the liver region is extracted from the image of each phase. Enhancement process is applied to the region by using a three-dimensional adaptive convergence index filter. The local maximum points are extracted from the enhanced image and the candidate regions for the liver tumor are extracted by applying the region-growing process. Multiple features are derived from the extracted candidates and it is decided whether or not the candidate actually corresponds to a tumor, based on the Mahalanobis distance calculated from the features. The processing from the enhancement to the discrimination of the candidates is performed independently for each phase, and four processed images are generated. Finally, the resultant images are combined and output. The proposed method is applied to 40 three-dimensional CT images of 1.0 patients taken by a multislice CT scanner. The result is promising, since all 8 existing tumors were detected, and the number of false-positive regions per image was 0.
机译:本文提出了一种从四个阶段(非对比,早期,门脉期,晚期)的三维腹部CT图像中提取肝肿瘤的自动方法。在提出的方法中,从每个阶段的图像中提取肝脏区域。通过使用三维自适应收敛指数滤波器对区域进行增强处理。从增强图像中提取局部最大值,并通过应用区域增长过程来提取肝肿瘤的候选区域。从提取出的候选物中导出多个特征,并基于从特征中计算出的马氏距离确定候选物是否实际上对应于肿瘤。对于每个阶段,独立执行从增强到候选候选的处理,并生成四个处理后的图像。最后,合成图像并输出。该方法应用于多层CT扫描仪拍摄的1.0例患者的40张三维CT图像。该结果令人鼓舞,因为已检测到所有8个现有肿瘤,每个图像的假阳性区域数为0。

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