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ChestXthon: An algorithm for Abnormality Detection in Chest Radiographs

机译:ChestXthon:胸部X光片中异常检测的算法

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Chest illnesses like heart failure, lung tumor or lung tuberculosis, and so on is frequently in view of chest X-ray images (CXR). The ailments are treatable on the off chance that they are recognized in their beginning times. Analyzing CXR is a tedious procedure. Now and again, therapeutic specialists had ignored the illnesses in their first examinations on CXR, and when the pictures were reevaluated, the malady signs could be detected. Furthermore, the quantity of CXR to look at is various and a long ways past the capacity of accessible therapeutic staff, particularly in creating nations. A PC supported finding (CAD) framework can check presumed zones on CXR for cautious examination by restorative specialists, and can give caution in the cases that need critical consideration. This paper reports our persistent work on developing an algorithm that aids the radiologists for the diagnosis of chest radiographs.
机译:考虑到胸部X射线图像(CXR),经常会出现心力衰竭,肺肿瘤或肺结核等胸部疾病。这些疾病可以在开始就被认可的偶然机会中得到治疗。分析CXR是一个繁琐的过程。治疗专家一次又一次在CXR上的第一次检查中就忽略了这些疾病,当重新评估照片时,就可以发现疾病迹象。此外,要看待CXR的数量千差万别,远远超出了可及的治疗人员的能力,尤其是在创建国家时。 PC支持的发现(CAD)框架可以检查CXR上的假定区域,以供修复专家进行仔细检查,并且在需要紧急考虑的情况下可以提供警告。本文报告了我们在开发一种算法方面的不懈努力,该算法可帮助放射科医生诊断胸部X光片。

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