Progression analysis and stage discovery in continuous physiological processes using image computing.
Progression analysis and stage discovery in continuous physiological processes using image computing.
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DOI：
10.1155/2010/107036
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Goldberg IG
中科院分区：
文献类型：
--
作者：
Shamir L;Rahimi S;Orlov N;Ferrucci L;Goldberg IG
我们提出了一种基于图像计算的方法，用于定量分析可以通过医学成像感知的连续生理过程，并展示其在分析与骨关节炎（OA）进展相关的骨结构形态变化中的应用。分析的目的是定量估计 OA 进展，以帮助了解该疾病的病理生理学。最终，纹理分析将能够提供一种替代的 OA 评分方法，与现有的临床使用的基于放射学的分类方案相比，该方法可能以更直接的方式反映疾病的进展。这种方法不仅可用于研究 OA 的性质，还可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可以通过医学成像诊断和预测的其他进行性临床病症。
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.