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A review on deep learning in medical image analysis

Authors :
S. Suganyadevi
K. Balasamy
V. Seethalakshmi
Source :
International Journal of Multimedia Information Retrieval
Publication Year :
2021
Publisher :
Springer London, 2021.

Abstract

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.

Details

Language :
English
ISSN :
2192662X and 21926611
Database :
OpenAIRE
Journal :
International Journal of Multimedia Information Retrieval
Accession number :
edsair.doi.dedup.....55a7858b7a58bbfcb7f43486e29e17b0