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Medical Image Analysis Using Deep Learning: A Systematic Literature Review

  • E. Sudheer KumarEmail author
  • C. Shoba Bindu
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 985)

Abstract

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.

Keywords

Big data analytics Medical Image Analysis Deep Learning Localization Segmentation Detection Classification 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringJNTUAAnanthapuramuIndia

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