.png){kind=icon}
返回
Preliminary Stages for COVID-19 Detection Using Image Processing
.png){kind=icon}
OA
AI
DOI：10.3390/diagnostics12123171.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
COVID-19 was first discovered in December 2019 in Wuhan. There have been reports of thousands of illnesses and hundreds of deaths in almost every region of the world. Medical images, when combined with cutting-edge technology such as artificial intelligence, have the potential to improve the efficiency of the public health system and deliver faster and more reliable findings in the detection of COVID-19. The process of developing the COVID-19 diagnostic system begins with image accusation and proceeds via preprocessing, feature extraction, and classification. According to literature review, several attempts to develop taxonomies for COVID-19 detection using image processing methods have been introduced. However, most of these adhere to a standard category that exclusively considers classification methods. Therefore, in this study a new taxonomy for the early stages of COVID-19 detection is proposed. It attempts to offer a full grasp of image processing in COVID-19 while considering all phases required prior to classification. The survey concludes with a discussion of outstanding concerns and future directions.
Keyword:
COVID-19
preprocessing
augmentation
segmentation
feature extraction
transfer learning
X-ray
CT
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.3
论文数:
2.0W
被引数:
3.6W
机构
引用论文
Desempenho de crianças do ensino fundamental na solução de problemas aritméticos<A NAME="top"></A>问题的基本解决方案 
OAAI
OAAI分享收藏分享收藏Variability in patterns of growth and morphology of Posidonia oceanica exposed to urban and industrial wastes: contrasts with two reference locations暴露于城市和工业废物的Posidonia oceanica的生长和形态的变化: 与两个参考位置的对比
PREAI
分享收藏Wider or Deeper: Revisiting the ResNet Model for Visual Recognition更广泛或更深入: 重新审视视觉识别的ResNet模型.png)
PATTERN RECOGNITIONOAAI
PATTERN RECOGNITIONIF7.6
OAAI分享收藏Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation, and Diagnosis for COVID-19新型冠状病毒肺炎成像数据采集，分割和诊断中的人工智能技术综述OAAI
OAAI分享收藏
查看更多内容