Image Registration Method from LDCT Image Using FFD Algorithm

Chika Tanaka, Tohru Kamiya, T. Aoki
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Abstract

In recent years, the number of lung cancer deaths has been increasing. In Japan, CT (Computed Tomography) equipment is used for its visual screening. However, there is a problem that seeing huge number of images taken by CT is a burden on the doctor. To overcome this problem, the CAD (Computer Aided Diagnosis) system is introduced on medical fields. In CT screening, LDCT (Low Dose Computed Tomography) screening is desirable considering radiation exposure. However, the image quality which is caused the lower the dose is another problem on the screening. A CAD system that enables accurate diagnosis even at low doses is needed. Therefore, in this paper, we propose a registration method for generating temporal subtraction images that can be applied to low-quality chest LDCT images. Our approach consists of two major components. Firstly, global matching based on the center of gravity is performed on the preprocessed images, and the region of interest (ROI) is set. Secondly, local matching by free-form deformation (FFD) based on B-Spline is performed on the ROI as final registration. In this paper, we apply our proposed method to LDCT images of 6 cases, and reduce 57.29% in the calculation time, 26.1% in the half value width, and 29.6% in the sum of histogram of temporal subtraction images comparing with the conventional method.
基于FFD算法的LDCT图像配准方法
近年来,肺癌死亡人数一直在增加。在日本,CT(计算机断层扫描)设备用于视觉筛查。但是,有一个问题是,看到大量的CT图像对医生来说是一种负担。为了解决这一问题,CAD(计算机辅助诊断)系统被引入到医疗领域。在CT筛查中,考虑到辐射暴露,LDCT(低剂量计算机断层扫描)筛查是可取的。但是,剂量越低所引起的图像质量问题是筛选上的另一个问题。需要一种即使在低剂量下也能进行准确诊断的CAD系统。因此,在本文中,我们提出了一种配准方法,用于生成可应用于低质量胸部LDCT图像的时间减法图像。我们的方法由两个主要部分组成。首先,对预处理后的图像进行基于重心的全局匹配,设置感兴趣区域(ROI);其次,对感兴趣区域进行基于b样条的自由变形(FFD)局部匹配作为最终配准;在本文中,我们将该方法应用于6例LDCT图像,与传统方法相比,计算时间缩短了57.29%,半值宽度缩短了26.1%,时间相减图像的直方图和缩短了29.6%。
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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