Article

Neural Architecture Search for Adversarial Medical Image Segmentation

Authors:

Eric XingAuthors Info & Claims

Medical Image Computing and Computer Assisted Intervention – MICCAI 2019: 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part VI

Pages 828 - 836

https://doi.org/10.1007/978-3-030-32226-7_92

Published: 13 October 2019 Publication History

Abstract

Adversarial training has led to breakthroughs in many medical image segmentation tasks. The network architecture design of the adversarial networks needs to leverage human expertise. Despite the fact that discriminator plays an important role in the training process, it is still unclear how to design an optimal discriminator. In this work, we propose a neural architecture search framework for adversarial medical image segmentation. We automate the process of neural architecture design for the discriminator with continuous relaxation and gradient-based optimization. We empirically analyze and evaluate the proposed framework in the task of chest organ segmentation and explore the potential of automated machine learning in medical applications. We further release a benchmark dataset for chest organ segmentation.

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Cited By

Yang DXu ZHe YNath VLi WMyronenko AHatamizadeh AZhao CRoth HXu D(2023)DAST: Differentiable Architecture Search with Transformer for 3D Medical Image SegmentationMedical Image Computing and Computer Assisted Intervention – MICCAI 202310.1007/978-3-031-43898-1_71(747-756)Online publication date: 8-Oct-2023
https://dl.acm.org/doi/10.1007/978-3-031-43898-1_71
Ahmed MAlZoubi ADu H(2021)Improving Generalization of ENAS-Based CNN Models for Breast Lesion Classification from Ultrasound ImagesMedical Image Understanding and Analysis10.1007/978-3-030-80432-9_33(438-453)Online publication date: 12-Jul-2021
https://dl.acm.org/doi/10.1007/978-3-030-80432-9_33
Zhu YMeijering E(2020)Neural Architecture Search for Microscopy Cell SegmentationMachine Learning in Medical Imaging10.1007/978-3-030-59861-7_55(542-551)Online publication date: 4-Oct-2020
https://dl.acm.org/doi/10.1007/978-3-030-59861-7_55
Show More Cited By

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Neural Architecture Search for Adversarial Medical Image Segmentation
1. Applied computing

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Information & Contributors

Information

Published In

cover image Guide Proceedings

Medical Image Computing and Computer Assisted Intervention – MICCAI 2019: 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part VI

Oct 2019

894 pages

ISBN:978-3-030-32225-0

DOI:10.1007/978-3-030-32226-7

Editors:
Dinggang Shen
University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
,
Tianming Liu
University of Georgia, Athens, GA, USA
,
Terry M. Peters
Western University, London, ON, Canada
,
Lawrence H. Staib
Yale University, New Haven, CT, USA
,
Caroline Essert
University of Strasbourg, Illkirch, France
,
Sean Zhou
United Imaging Intelligence, Shanghai, China
,
Pew-Thian Yap
University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
,
Ali Khan
Western University, London, ON, Canada

© Springer Nature Switzerland AG 2019.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 13 October 2019

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Cited By

Yang DXu ZHe YNath VLi WMyronenko AHatamizadeh AZhao CRoth HXu D(2023)DAST: Differentiable Architecture Search with Transformer for 3D Medical Image SegmentationMedical Image Computing and Computer Assisted Intervention – MICCAI 202310.1007/978-3-031-43898-1_71(747-756)Online publication date: 8-Oct-2023
https://dl.acm.org/doi/10.1007/978-3-031-43898-1_71
Ahmed MAlZoubi ADu H(2021)Improving Generalization of ENAS-Based CNN Models for Breast Lesion Classification from Ultrasound ImagesMedical Image Understanding and Analysis10.1007/978-3-030-80432-9_33(438-453)Online publication date: 12-Jul-2021
https://dl.acm.org/doi/10.1007/978-3-030-80432-9_33
Zhu YMeijering E(2020)Neural Architecture Search for Microscopy Cell SegmentationMachine Learning in Medical Imaging10.1007/978-3-030-59861-7_55(542-551)Online publication date: 4-Oct-2020
https://dl.acm.org/doi/10.1007/978-3-030-59861-7_55
Peng YBi LFulham MFeng DKim J(2020)Multi-modality Information Fusion for Radiomics-Based Neural Architecture SearchMedical Image Computing and Computer Assisted Intervention – MICCAI 202010.1007/978-3-030-59728-3_74(763-771)Online publication date: 4-Oct-2020
https://dl.acm.org/doi/10.1007/978-3-030-59728-3_74
Kügler DUecker MKuijper AMukhopadhyay A(2020)AutoSNAP: Automatically Learning Neural Architectures for Instrument Pose EstimationMedical Image Computing and Computer Assisted Intervention – MICCAI 202010.1007/978-3-030-59716-0_36(375-384)Online publication date: 4-Oct-2020
https://dl.acm.org/doi/10.1007/978-3-030-59716-0_36

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