论文标题
类风湿关节炎的关节空间狭窄进展的子像素准确量化
A Sub-pixel Accurate Quantification of Joint Space Narrowing Progression in Rheumatoid Arthritis
论文作者
论文摘要
类风湿关节炎(RA)是一种慢性自身免疫性疾病,主要影响外周关节,例如手指,手腕和脚。放射学在RA的诊断和监测中起着至关重要的作用。受射线照相成像的当前空间分辨率的限制,以上相同原因的RA的关节空间变窄(JSN)的进展可能少于每年的像素,并且具有通用空间分辨率。对JSN的不敏感监测会阻碍放射科医生/风湿病专家做出适当,及时的临床判断。在本文中,我们提出了一种新颖敏感的方法,我们称之为部分图像相关的相关性,旨在自动量化RA早期阶段的JSN进程。当前的大多数文献都利用平均误差,根平方偏差和标准偏差来报告像素级别的准确性。我们的工作通过使用频域中的相光谱来测量基线与其后续手指关节图像之间的JSN进程。使用这项研究,将平均误差用于具有地面真相的幻影X光片,以及0.0519mm的临床射线照相偏差。由于其子像素精度远远超出了手动测量,我们乐观地认为我们的工作有望自动量化JSN的进展。
Rheumatoid arthritis (RA) is a chronic autoimmune disease that primarily affects peripheral synovial joints, like fingers, wrist and feet. Radiology plays a critical role in the diagnosis and monitoring of RA. Limited by the current spatial resolution of radiographic imaging, joint space narrowing (JSN) progression of RA with the same reason above can be less than one pixel per year with universal spatial resolution. Insensitive monitoring of JSN can hinder the radiologist/rheumatologist from making a proper and timely clinical judgment. In this paper, we propose a novel and sensitive method that we call partial image phase-only correlation which aims to automatically quantify JSN progression in the early stages of RA. The majority of the current literature utilizes the mean error, root-mean-square deviation and standard deviation to report the accuracy at pixel level. Our work measures JSN progression between a baseline and its follow-up finger joint images by using the phase spectrum in the frequency domain. Using this study, the mean error can be reduced to 0.0130mm when applied to phantom radiographs with ground truth, and 0.0519mm standard deviation for clinical radiography. With its sub-pixel accuracy far beyond manual measurement, we are optimistic that our work is promising for automatically quantifying JSN progression.