Smart Health in Medical Image Analysis

Haifeng Wang (), Qianqian Zhang (), Daehan Won () and Sang Won Yoon ()
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Haifeng Wang: State University of New York at Binghamton
Qianqian Zhang: State University of New York at Binghamton
Daehan Won: State University of New York at Binghamton
Sang Won Yoon: State University of New York at Binghamton

A chapter in Optimization in Large Scale Problems, 2019, pp 221-242 from Springer

Abstract: Abstract Medical imaging can facilitate diagnoses, treatment, and surgical planning, and increase clinical productivity. However, manual assessments of medical images require time-consuming works and lead to subjective conclusions. Through application of artificial intelligence (AI), automatic medical image analysis can be achieved to improve the accuracy and efficiency of healthcare services. This chapter describes two deep learning-based AI techniques for medical image analysis, e.g., tissue classification and medical image data augmentation. For each example, the algorithms are described first. Then the experiment results are presented to show the potential performance of using AI to enhance smart health. Conclusions and future directions are summarized at the end of the chapter.

Keywords: Artificial intelligence; Medical image analysis; Smart health (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-030-28565-4_20

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DOI: 10.1007/978-3-030-28565-4_20

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