Cirrhosis is a liver disease resulting from abnormal continuation of fibrosis, and ultrasound imaging is widely used for cirrhosis diagnosis because of its non‐invasiveness. However, due to unclear appearances of cirrhosis on ultrasound images, diagnoses are difficult and individual results possibly differ depending on the physician's experience. Recently, computer‐aided diagnostic systems using image processing and machine learning have been developed to help physicians detect cirrhosis as a ‘Second opinion’. Some related studies have focused on a scenario where physicians set ROIs (Region of Interests) manually because selecting reliable ROIs for training a classifier and classification of patients is indispensable. But, the accuracy of such systems depends inherently on the quality of ROIs, and thus the workloads of physicians increase. In this paper, we propose a reliability evaluation method (REM) for each ROI based on its posterior probability and relationship to peripheral ROIs. The assumption of our proposal is that reliable regions of cirrhosis and normal can be observed in certain regions predominantly. We evaluated the effectiveness of the REM and its optimization for practical use. Experimental results showed that our proposed method curated reliable ROIs and improved classification performance in terms of AUC (Area Under the Curve). © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

中文翻译：

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使用超声图像检测肝硬化的可靠性评估方法自动选择 ROI

肝硬化是纤维化异常持续而导致的肝脏疾病，超声成像因其无创性而被广泛用于肝硬化诊断。然而，由于超声图像上肝硬化的表现不清晰，诊断很困难，并且根据医生的经验，个体结果可能会有所不同。最近，使用图像处理和机器学习的计算机辅助诊断系统已被开发出来，可以帮助医生作为“第二意见”来检测肝硬化。一些相关研究主要集中在医生手动设置 ROI（感兴趣区域）的场景，因为选择可靠的 ROI 来训练分类器和对患者进行分类是必不可少的。但是，此类系统的准确性本质上取决于 ROI 的质量，因此医生的工作量会增加。在本文中，我们根据每个 ROI 的后验概率以及与外围 ROI 的关系，提出了一种可靠性评估方法（REM）。我们建议的假设是，主要在某些区域可以观察到可靠的肝硬化区域和正常区域。我们评估了 REM 的有效性及其实际应用的优化。实验结果表明，我们提出的方法提供了可靠的 ROI，并提高了 AUC（曲线下面积）的分类性能。 © 2024 日本电气工程师协会和 Wiley periodicals LLC。