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首页> 外文期刊>Bulletin of the Polish Academy of Sciences. Technical Sciences >Finger joint synovitis detection in ultrasound images
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Finger joint synovitis detection in ultrasound images

机译：超声图像中的手指联合滑膜炎检测

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摘要

Ultrasonography has proved its usefulness in the evaluation of joint inflammations caused by rheumatoid arthritis.The illness severity is scored by human examiners based on their experience,but some discrepancies in the final diagnosis and treatment frequently occur.Therefore,the main aim of this work is the elaboration of an automatic method of the localization of finger joint inflammation level in ultrasound images.In this paper we propose a novel,fully automated framework for synovitis region segmentation.In our approach we compare several bones and joint localization methods based on the seeded region growing technique,which is combined with different speckle noise filtering algorithms.This technique extracts a region from the image using some predefined criteria of similarity between initially selected point and the pixels in its neighborhood.The seed point is localized automatically as the darkest patch within a small region between two detected finger bones close to the joint.The region affected by synovitis is found using the adopted criterion of homogeneity based on a patch to patch similarity measure.The obtained results exhibit a satisfying accuracy in comparison with the annotations prepared by an expert and the results delivered by semi-automatic methods that require manual bones delineation.
机译：超声检查在评估类风湿性关节炎引起的关节炎症方面已被证明是有用的。疾病的严重程度由人类检查人员根据他们的经验进行评分，但在最终诊断和治疗中经常出现一些差异。因此，这项工作的主要目的是阐述一种自动定位超声图像中手指关节炎症程度的方法。在本文中，我们提出了一种新的、全自动的滑膜炎区域分割框架。在我们的方法中，我们比较了几种基于种子区域生长技术的骨骼和关节定位方法，该技术与不同的斑点噪声滤波算法相结合。该技术使用初始选择点与其邻域像素之间的一些预定义相似性标准从图像中提取区域。种子点自动定位为靠近关节的两个检测到的手指骨骼之间的一个小区域内最暗的面片。使用所采用的基于贴片到贴片相似性度量的同质性标准来确定受滑膜炎影响的区域。与专家准备的注释和需要手动描绘骨骼的半自动方法交付的结果相比，所获得的结果显示出令人满意的准确性。

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