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Chest radiographs segmentation by the use of nature-inspired algorithm for lung disease detection

机译:使用自然启发算法对胸部X光片进行分割以检测肺部疾病

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Rapid detection of potential threads can speed up medical examination and help to start the treatment without delays. Automatic analysis of x-ray screening is a complex, multi-step process that can be beneficial for more efficient examinations in pulmonary clinics. Traditional methods use image segmentation to cut out interesting areas for further analysis of deviations from the norm (i.e., unhealthy tissues detection). However the area is extracted as a whole part, but for sensitive and more patient oriented examinations we need approach that will be extending segmentation only with necessary elements. In this article we present research results on application of heuristic method for detection over aggregated x-ray image that comes from implemented segmentation.
机译:快速检测潜在的线程可以加快医学检查的速度,并有助于立即开始治疗。 X射线筛查的自动分析是一个复杂的,多步骤的过程,对于在肺部诊所进行更有效的检查可能是有益的。传统方法使用图像分割来切出有趣的区域,以进一步分析与标准的偏差(即,不健康的组织检测)。但是,该区域是作为一个整体提取的,但是对于敏感且面向患者的检查,我们需要一种仅使用必要元素扩展分割的方法。在本文中,我们介绍了启发式方法在来自已实现的分割的聚合x射线图像检测中的应用研究成果。

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