使用深度学习算法检测肺炎

Dirisala Saikrishna, Mulagala Madhusudhan Rao, B. Dhanush, S. Harshavardhan, Borra Prudhvi, Pooja Rana, Usha Mittal
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引用次数: 3

摘要

由细菌感染引起的肺部疾病是肺炎。在有效的治疗过程中,早期诊断是一个重要的因素。这种疾病通常由放射科专家通过胸部x射线图像来识别。出于某些目的,诊断可能是主观的,例如在胸部x线图像中可能不清楚疾病的存在或可能与其他疾病混淆。因此,计算机辅助诊断系统对于指导临床医生是必要的。本研究回顾了几篇基于深度学习和卷积神经网络的肺炎计算机辅助自动检测的研究论文,比较了不同模型的性能和准确性,并总结了未来的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pneumonia Detection Using Deep Learning Algorithms
A disease that occurs in the lungs caused by a bacterial infection is pneumonia. In terms of the effective process of treatment, early diagnosis is a significant factor. The disease will usually be identified by an expert radiologist using chest X-ray images. For certain purposes, diagnosis can be subjective, such as the presence of diseases that may be unclear in chest X-ray images or may be confused with other diseases. Computer-aided diagnostic systems are therefore necessary to direct the clinicians. In this study, several research papers about automated computer-aided detection of pneumonia with help of deep learning and convolutional neural networks were reviewed and different models were compared based on their performance and accuracy along with a conclusion and future work.
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