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Automatic finger joint synovitis localization in ultrasound images

机译:超声图像中自动手指联合滑膜炎定位

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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,关节的长期炎症导致其他人之间。未治疗时,可能会影响其他器官和一般患者的健康。因此,早期检测和运行适当的医疗具有重要价值。患者的器官用高频声波扫描,从而通过超声超声检查(USG)图像能够可视化内部身体结构。然而,该过程是标准化的,不同的预测结果导致各种可能的数据,这应该在短时间内由医生使用医疗地图集作为指导。这项工作介绍了一种基于统计方法的有效框架,它能够自动定位皮肤和骨区,然后用于指向手指联合滑膜炎区域的定位。处理流水线实时实现任务,并在专家准备的注释相比时证明高精度。

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