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Automatic Radiographic Quantification of Joint Space Narrowing Progression in Rheumatoid Arthritis Using POC

机译:使用POC对类风湿关节炎的关节间隙狭窄进行自动放射线照相定量

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This paper is an application of image processing techniques for computer-aided diagnosis of Rheumatoid Arthritis (RA). Accurately measuring the progression of joint space narrowing (JSN) is crucial during medical treatment and in imaging biomarkers in clinical trials. In this paper, we analyze sequential radiographic images of patients who have rheumatoid arthritis in hands using image processing techniques. Phase only correlation (POC) is used to detect the progression of JSN between images. A new image processing algorithm is proposed to segment joint images so as to eliminate the mutual interference when measuring the movement of the upper and lower bones by POC. We found that the texture feature on bones will greatly affect the accuracy of POC. Median filter is used to eliminate the effect of texture, and excellent results are obtained in practice. Additionally, the progress of JSN is measured accurately in our method. This can be beneficial for doctors in the identification of disease stages.
机译:本文是图像处理技术在类风湿关节炎(RA)计算机辅助诊断中的应用。在医学治疗和临床试验中对生物标志物成像期间,准确测量关节间隙变窄(JSN)的进展至关重要。在本文中,我们使用图像处理技术分析了手中风湿性关节炎患者的放射影像学图像。仅相位相关性(POC)用于检测图像之间JSN的进度。提出了一种新的图像处理算法,对关节图像进行分割,以消除POC测量上下骨骼运动时的相互干扰。我们发现骨骼上的纹理特征将极大地影响POC的准确性。使用中值滤镜消除纹理效果,在实践中获得了极好的效果。此外,在我们的方法中可以准确地测量JSN的进度。这对于医生识别疾病阶段可能是有益的。

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