4.6 Review

A review on deep learning in medical image analysis

出版社

SPRINGER
DOI: 10.1007/s13735-021-00218-1

关键词

Deep learning; Survey; Image classes; Medical image analysis; Accuracy

向作者/读者索取更多资源

Ongoing advances in AI, particularly in deep learning techniques, have been crucial in identifying, classifying, and quantifying patterns in clinical images. The rapid development of deep learning has found effective applications in various medical fields, including neurology, pathology, radiology, and more. This paper presents research on the application of deep learning in medical image processing, showcasing both fundamental information and cutting-edge approaches in this area.
Ongoing improvements in AI, particularly concerning deep learning techniques, are assisting to identify, classify, and quantify patterns in clinical images. Deep learning is the quickest developing field in artificial intelligence and is effectively utilized lately in numerous areas, including medication. A brief outline is given on studies carried out on the region of application: neuro, brain, retinal, pneumonic, computerized pathology, bosom, heart, breast, bone, stomach, and musculoskeletal. For information exploration, knowledge deployment, and knowledge-based prediction, deep learning networks can be successfully applied to big data. In the field of medical image processing methods and analysis, fundamental information and state-of-the-art approaches with deep learning are presented in this paper. The primary goals of this paper are to present research on medical image processing as well as to define and implement the key guidelines that are identified and addressed.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据