Progression analysis and stage discovery in continuous physiological processes using image computing.

Lior Shamir, Salim Rahimi, Nikita Orlov, Luigi Ferrucci, Ilya G Goldberg
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引用次数: 12

Abstract

We propose an image computing-based method for quantitative analysis of continuous physiological processes that can be sensed by medical imaging and demonstrate its application to the analysis of morphological alterations of the bone structure, which correlate with the progression of osteoarthritis (OA). The purpose of the analysis is to quantitatively estimate OA progression in a fashion that can assist in understanding the pathophysiology of the disease. Ultimately, the texture analysis will be able to provide an alternative OA scoring method, which can potentially reflect the progression of the disease in a more direct fashion compared to the existing clinically utilized classification schemes based on radiology. This method can be useful not just for studying the nature of OA, but also for developing and testing the effect of drugs and treatments. While in this paper we demonstrate the application of the method to osteoarthritis, its generality makes it suitable for the analysis of other progressive clinical conditions that can be diagnosed and prognosed by using medical imaging.

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用图像计算连续生理过程的进展分析和阶段发现。
我们提出了一种基于图像计算的方法,用于定量分析医学成像可以感知的连续生理过程,并演示了其在分析与骨关节炎(OA)进展相关的骨结构形态学改变方面的应用。分析的目的是定量估计骨性关节炎的进展,以帮助理解疾病的病理生理学。最终,纹理分析将能够提供一种替代OA评分方法,与现有临床使用的基于放射学的分类方案相比,该方法可以更直接地反映疾病的进展。这种方法不仅可以用于研究OA的性质,还可以用于开发和测试药物和治疗的效果。虽然在本文中我们展示了该方法在骨关节炎中的应用,但其通用性使其适用于分析其他可通过医学影像学诊断和预测的进展性临床疾病。
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