Ultrasound (US) medical imaging rises as a technique usedto 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 thedesign and implementation of the software toolkit HAPAN (HAPANis a Spanish acronym for H erramienta de Asistencia para la Pr actica de Anestesia en N ervios perif´ericos-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.
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