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Developing and verifying automatic detection of active pulmonary tuberculosis from multi-slice spiral CT images based on deep learning

机译:基于深度学习的多层螺旋CT图像自动检测自动检测活性肺结核

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OBJECTIVE: Diagnosis of tuberculosis (TB) in multi-slice spiral computed tomography (CT) images is a difficult task in many TB prevalent locations in which experienced radiologists are lacking. To address this difficulty, we develop an automated detection system based on artificial intelligence (AI) in this study to simplify the diagnostic process of active tuberculosis (ATB) and improve the diagnostic accuracy using CT images.
机译:目的:多层螺旋计算断层扫描(CT)图像中结核病(TB)的诊断是许多TB普遍存在的地点缺乏的艰难任务。 为了解决这种困难,我们在本研究中开发了一种基于人工智能(AI)的自动检测系统,以简化活性结核病(ATB)的诊断过程,并通过CT图像提高诊断精度。

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