Preface

Gobert Lee; Hiroshi Fujita

doi:10.1007/978-3-030-33128-3

Preface

Gobert Lee
, Hiroshi Fujita

College of Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Foreword/postscript

1 Citation (Scopus)

Abstract

Deep learning is at the leading edge of artificial intelligence (AI) and is
developing rapidly. In recent years, it has played an increasingly important
role in medical image analysis. Deep learning is a subfield of machine
learning and is based on deep neural networks (DNNs)—neural networks
with more than one hidden layer. Convolutional neural networks (CNNs)
are a subclass of DNNs that are especially useful for image recognition
and classification and have been attracting a lot of interest from industry,
academia, and clinicians.

Original language	English
Title of host publication	Deep learning in medical image analysis
Subtitle of host publication	Challenges and applications
Editors	Gobert Lee, Hiroshi Fujita
Place of Publication	Switzerland
Publisher	Springer Nature
Pages	v-vi
Number of pages	2
ISBN (Electronic)	978-3-030-33128-3
ISBN (Print)	978-3-030-33127-6, 978-3-030-33130-6
DOIs	https://doi.org/10.1007/978-3-030-33128-3
Publication status	Published - 2020

Publication series

Name	Advances in Experimental Medicine and Biology
Publisher	Springer, Cham
Volume	1213
ISSN (Print)	0065-2598
ISSN (Electronic)	2214-8019

Keywords

Deep learning
Deep neural network
Convolutional neural network
Medical image analysis
Computer aided diagnosis
Breast cancer detection
Lung nodule detection
Pulmonary image analysis
Multi organ segmentation
Retinopathy

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Preface

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Keywords

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