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Automatic finger joint synovitis localization in ultrasound images

机译:手指关节滑膜炎在超声图像中的自动定位

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A long-lasting inflammation of joints results between others in many arthritis diseases. When not cured, it may influence other organs and general patients' health. Therefore, early detection and running proper medical treatment are of big value. The patients' organs are scanned with high frequency acoustic waves, which enable visualization of interior body structures through an ultrasound sonography (USG) image. However, the procedure is standardized, different projections result in a variety of possible data, which should be analyzed in short period of time by a physician, who is using medical atlases as a guidance. This work introduces an efficient framework based on statistical approach to the finger joint USG image, which enables automatic localization of skin and bone regions, which are then used for localization of the finger joint synovitis area. The processing pipeline realizes the task in real-time and proves high accuracy when compared to annotation prepared by the expert.
机译:在许多关节炎疾病中,关节之间会长期持续发炎。如果不治愈,可能会影响其他器官和一般患者的健康。因此,早期发现和进行适当的医疗治疗具有重要的价值。用高频声波扫描患者的器官,从而通过超声超声(USG)图像可视化内部身体结构。但是,该过程是标准化的,不同的预测会产生各种可能的数据,应由以医疗地图集为指导的医师在短时间内进行分析。这项工作为手指关节USG图像引入了一种基于统计方法的有效框架,该框架能够自动定位皮肤和骨骼区域,然后将其用于手指关节滑膜炎区域的定位。与专家准备的注释相比,处理流水线可实时实现任务并证明具有较高的准确性。

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