A literature review of pneumonia detection algorithms based on deep learning and chest X-ray imaging

Chenyu Wang
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Abstract

Pneumonia is a serious disease that poses a threat to people’s health of all ages. It could happen when people are infected by viruses, fungi, bacteria etc. Typically, Chest X-rays are the first and foremost imaging approach to implement pneumonia detection. This paper introduces the latest research achievements to help those who are new in this field to have basic intuition about AI in pneumonia detection., including Vision Transformers on chest X-ray, a novel model based on RetinaNet, CP_DeepNet, and a novel Efficient NetV2L model. The last part gives some suggestions about the future study of pneumonia detection using Deep learning.
基于深度学习和胸部 X 光成像的肺炎检测算法文献综述
肺炎是一种严重的疾病,对所有年龄段的人的健康都构成威胁。当人们受到病毒、真菌、细菌等感染时,就有可能患上肺炎。通常情况下,胸部 X 光是检测肺炎的首要成像方法。本文介绍了最新的研究成果,以帮助初涉此领域的人员对人工智能在肺炎检测中的应用有基本的直观认识,包括胸部 X 射线上的视觉变换器、基于 RetinaNet 的新型模型、CP_DeepNet 和新型 Efficient NetV2L 模型。最后一部分对未来利用深度学习进行肺炎检测的研究提出了一些建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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