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HAPAN: Support Tool for Practicing Regional Anesthesia in Peripheral Nerves

机译:HAPAN:进行周围神经区域麻醉的支持工具

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Ultrasound (US) medical imaging rises as a technique used to visualize nerve structures, among other applications. It has been used, typically, as a tool for assisting in the practice of peripheral nerve anesthesia. Due to its non-invasive nature, US may reduce the risk of injury to medical patients during surgical procedures. Despite its usefulness, it is challenging for anesthesiologists to perform the anesthesia process, mainly due to the presence of speckle and acoustic multiplicative noise, significantly degrading the image quality. Besides, the lack of homogeneity in the imaged structures disorients the anesthesiologist in the effective localization of the nerve structure. In this paper, we present the design and implementation of the software toolkit HAPAN (HAPAN is a Spanish acronym for Herrarnienta de Asistencia para la Prdctica de Anestesia en Nervios perifericos-Assistance tool for the anesthesia of peripheral nerves.), developed in MATLAB, for the segmentation of different peripheral nerves in ultrasound images. HAPAN includes algorithms for automatic nerve segmentation based on appearance shape models, and image resolution enhancement.
机译:超声(美国)医学成像技术是一种用于可视化神经结构的技术,其应用领域尤其广泛。通常,它已被用作辅助进行周围神经麻醉的工具。由于其无创性,US可以减少外科手术过程中医疗患者受伤的风险。尽管其有用,但是麻醉师执行麻醉过程仍然是一个挑战,这主要是由于斑点和声学倍增噪声的存在,从而大大降低了图像质量。此外,成像结构缺乏均一性使麻醉医师在神经结构的有效定位方面感到困惑。在本文中,我们介绍了软件工具箱HAPAN的设计和实现(HAPAN是西班牙语的缩写,它代表了周围神经麻醉的辅助麻醉工具Nervios perifericos-Aneresia en Nervios perifericos-)。超声图像中不同周围神经的分割。 HAPAN包括基于外观形状模型和图像分辨率增强的自动神经分割算法。

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