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Medical Image Analysis Using Deep Learning: A Systematic Literature Review - 2019

Medical Image Analysis Using Deep Learning: A Systematic Literature Review

Research Area:  Machine Learning


The field of big data analytics has started playing a vital role in the advancement of Medical Image Analysis (MIA) over the last decades very quickly. Healthcare is a major example of how the three Vs of data i.e., velocity, variety, and volume, are an important feature of the data it generates. In medical imaging (MI), the exact diagnosis of the disease and/or assessment of disease relies on both image collection and interpretation. Image interpretation by the human experts is a bit difficult with respect to its discrimination, the complication of the image, and also the prevalent variations exist across various analyzers. Recent improvements in Machine Learning (ML), specifically in Deep Learning (DL), help in identifying, classifying and measuring patterns in medical images. This paper is focused on the Systematic Literature Review (SLR) of various microservice events like image localization, segmentation, detection, and classification tasks.


Author(s) Name:  E. Sudheer Kumar & C. Shoba Bindu

Journal name:  

Conferrence name:  International Conference on Emerging Technologies in Computer Engineering

Publisher name:  Springer

DOI:  10.1007/978-981-13-8300-7_8

Volume Information: