Kim Kwang-Baek, Kim Chang Won, Kim Gwang Ha
Division of Computer and Information Engineering, Silla University, Sasang-Gu, Busan, Republic of Korea.
J Digit Imaging. 2008 Oct;21 Suppl 1(Suppl 1):S89-103. doi: 10.1007/s10278-007-9053-4. Epub 2007 Sep 6.
In Korea, hepatocellular carcinoma is the third frequent cause of cancer death, occupying 17.2% among the whole deaths from cancer, and the rate of death from hepatocellular carcinoma comes to about 21 out of 100,000. This paper proposes an automatic method for the extraction of areas being suspicious as hepatocellular carcinoma from computed tomography (CT) scans and evaluates the availability as an auxiliary tool for the diagnosis of hepatocellular carcinoma. For detecting tumors in the internal of the liver from a CT scan, first, an area of the liver is extracted from about 45-50 CT slices obtained by scanning in 2.5-mm intervals starting from the lower part of the chest. In the extraction of an area of the liver, after the unconcerned areas outside of the bony thorax are removed, areas of the internal organs are segmented by using information on the intensity distribution of each organ, and an area of the liver is extracted among the segmented areas by using information on the position and morphology of the liver. Because hepatocellular carcinoma is a hypervascular tumor, the area corresponding to hepatocellular carcinoma appears more brightly than the surroundings in a CT scan, and also takes a spherical shape if the tumor shows expansile growth pattern. By using these features, areas being brighter than the surroundings and globe-shaped are segmented as candidate areas for hepatocellular carcinoma in the area of the liver, and then, areas appearing at the same position in successive CT slices among the candidates are discriminated as hepatocellular carcinoma. For the performance evaluation of the proposed method, experimental results obtained by applying the proposed method to CT scans were compared with the diagnoses by radiologists. The evaluation results showed that all areas of the liver and hypervascular tumors were extracted exactly and the proposed method has a high availability as an auxiliary diagnosis tool for the discrimination of liver tumors.
在韩国,肝细胞癌是癌症死亡的第三大常见原因,占癌症总死亡人数的17.2%,肝细胞癌的死亡率约为每10万人中有21人。本文提出了一种从计算机断层扫描(CT)图像中自动提取疑似肝细胞癌区域的方法,并评估其作为肝细胞癌诊断辅助工具的可用性。为了从CT扫描中检测肝脏内部的肿瘤,首先,从胸部下部开始以2.5毫米间隔扫描获得的约45 - 50层CT切片中提取肝脏区域。在提取肝脏区域时,先去除胸廓外的无关区域,然后利用各器官的强度分布信息对内部器官区域进行分割,再利用肝脏的位置和形态信息从分割后的区域中提取肝脏区域。由于肝细胞癌是一种富血管肿瘤,在CT扫描中,对应肝细胞癌的区域比周围区域显得更亮,如果肿瘤呈膨胀性生长模式,其形状也呈球形。利用这些特征,将肝脏区域中比周围区域亮且呈球形的区域分割为肝细胞癌的候选区域,然后,从这些候选区域中识别出在连续CT切片中出现在同一位置的区域作为肝细胞癌。为了对所提方法进行性能评估,将该方法应用于CT扫描得到的实验结果与放射科医生的诊断结果进行了比较。评估结果表明,肝脏和富血管肿瘤的所有区域都被准确提取,所提方法作为鉴别肝脏肿瘤的辅助诊断工具具有很高的可用性。