Article

Thyroid Nodule Segmentation in Ultrasound Images Based on Cascaded Convolutional Neural Network

Authors:

Mei Yu,

Kai LiuAuthors Info & Claims

Neural Information Processing: 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13–16, 2018, Proceedings, Part VI

Pages 373 - 384

https://doi.org/10.1007/978-3-030-04224-0_32

Published: 13 December 2018 Publication History

Abstract

Based on U-shaped Fully Convolutional Neural Network (UNET), Convolutional Neural Network (CNN) classifier and Deep Fully Convolutional Neural Network (FCN), this paper proposes a thyroid nodule segmentation model in form of cascaded convolutional neural network. In this paper, we study the segmentation of thyroid nodules from two aspects, segmentation process and model structure. On the one hand, the research of the segmentation process includes the gradual reduction of the segmentation region and the selection of different model structures. On the other hand, the research of model structures includes the design of network structure, the adjustment of model parameters and so on. And the experiment shows that our thyroid nodule segmentation in ultrasound images has a good performance, which is superior to the current algorithms and can be used as a reference for the diagnosis of the doctor.

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Cited By

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Oza UGohel BKumar POza P(2024)Presegmenter Cascaded Framework for Mammogram Mass SegmentationJournal of Biomedical Imaging10.1155/2024/94220832024Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1155/2024/9422083
Chen CXu BWu YWu KTan C(2022)Research on Ultrasonic Image Segmentation of Thyroid Nodules Based on Improved U-net++Proceedings of the 2022 2nd International Conference on Bioinformatics and Intelligent Computing10.1145/3523286.3524603(532-536)Online publication date: 21-Jan-2022
https://dl.acm.org/doi/10.1145/3523286.3524603

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Published In

Neural Information Processing: 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13–16, 2018, Proceedings, Part VI

Dec 2018

595 pages

ISBN:978-3-030-04223-3

DOI:10.1007/978-3-030-04224-0

Editors:
Long Cheng
The Chinese Academy of Sciences, Beijing, China
,
Andrew Chi Sing Leung
City University of Hong Kong, Kowloon, Hong Kong
,
Seiichi Ozawa
Kobe University, Kobe, Japan

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 13 December 2018

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Oza UGohel BKumar POza P(2024)Presegmenter Cascaded Framework for Mammogram Mass SegmentationJournal of Biomedical Imaging10.1155/2024/94220832024Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1155/2024/9422083
Chen CXu BWu YWu KTan C(2022)Research on Ultrasonic Image Segmentation of Thyroid Nodules Based on Improved U-net++Proceedings of the 2022 2nd International Conference on Bioinformatics and Intelligent Computing10.1145/3523286.3524603(532-536)Online publication date: 21-Jan-2022
https://dl.acm.org/doi/10.1145/3523286.3524603

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A review of thyroid gland segmentation and thyroid nodule segmentation methods for medical ultrasound images

Brain Lacunae Segmentation from Fair Sequence Based On Fully Convolutional Neural Network

Prior Region Mask R-CNN for Thyroid Nodule Segmentation in Ultrasound Images

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