Image Registration Method from LDCT Image Using FFD Algorithm

被引:0
|
作者
Tanaka, Chika [1 ]
Kamiya, Tohru [1 ]
Aoki, Takatoshi [2 ]
机构
[1] Kyushu Inst Technol, 1-1 Sensui, Kitakyushu, Fukuoka 8048550, Japan
[2] Univ Occupat & Environm Hlth, Kitakyushu, Fukuoka, Japan
来源
2020 20TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS) | 2020年
关键词
Computer Aided Diagnosis; Low Dose Computed Tomography; Registration; Free-Form Deformation;
D O I
10.23919/iccas50221.2020.9268267
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:411 / 414
页数:4
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