On Visualization and Quantification of Lesion Margin in CT Liver Images

S. Arıca, Tuğçe Sena Altuntaş, G. Erbay
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Abstract

Cancer is the one of the leading causes of death worldwide, and cancer incidence increases every year. The analysis of lesion margin is quite important to diagnose malignant and benign masses and to detect the presence and the stage of tumor invasion in case of cancer. Accordingly, the aim of the study is to visualize and quantify margin of lesions on radiological images by means of a digital computer. In this study, computed tomography (CT) images of liver have been employed for analysis because the liver has crucial tasks in our body and liver cancer-related deaths is ranked as the forth among the cancer-related deaths. The proposed method consisted of four main steps: image cropping and smoothing, specification of target lesion, the boundary detection of target lesion, and visualization and quantification of margin. First, the images were converted to gray scale. The blank regions surrounding the liver in the CT images were removed before specification of target lesion, and further were smoothed with a bilateral filter. Next, the target region was specified roughly by drawing it manually. The boundary of lesion was more precisely determined with the active contour method employing the sketched borderline as the initial curve. Next, the properties of the target region: the centroid, major axis length, and the orientation values were computed. The intensities along a line passing through the center of the tumor were obtained for eighteen different rotation angles. A pulse model was fit to each of the intensity signal corresponding to a rotation. Then, the intensity change, margin sharpness and width were acquired from the pulse approximation associated to each rotation angle. The level difference provided the intensity change, the slope of edges gave the margin sharpness, and distance between the start and end points of the pulse edge represented margin width. Besides, the inner (core) and outer diameter with respect to angle were also displayed.
肝脏CT图像病灶边缘的可视化与定量研究
癌症是世界范围内死亡的主要原因之一,癌症发病率每年都在增加。病灶边缘的分析对于诊断恶性肿块和良性肿块,判断肿瘤是否存在及侵袭分期具有重要意义。因此,本研究的目的是通过数字计算机在放射图像上可视化和量化病灶的边缘。在本研究中,肝脏的计算机断层扫描(CT)图像被用于分析,因为肝脏在我们的身体中起着至关重要的作用,肝癌相关死亡在癌症相关死亡中排名第四。该方法包括图像裁剪与平滑、目标病灶指定、目标病灶边界检测、边缘可视化与量化四个主要步骤。首先,将图像转换为灰度。在确定目标病灶之前,先去除CT图像中肝脏周围的空白区域,然后用双侧滤波器进行平滑处理。接下来,通过手工绘制粗略指定目标区域。活动轮廓法以绘制的轮廓线为初始曲线,更精确地确定病灶的边界。接下来,计算目标区域的属性:质心、长轴长度和方向值。在18个不同的旋转角度下,获得沿一条穿过肿瘤中心的线的强度。对每一个旋转对应的强度信号进行脉冲模型拟合。然后,通过与每个旋转角度相关联的脉冲近似,获得光强变化、边缘锐度和宽度;等高差提供了强度变化,边缘的斜率给出了边缘锐度,脉冲边缘的起始点和结束点之间的距离表示边缘宽度。此外,还显示了内(芯)外径与角度的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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