Deep neural network for pancreas segmentation from CT images

Zhanlan Chen; Jiangbin Zheng

doi:10.1007/978-3-030-39431-8_39

Deep neural network for pancreas segmentation from CT images

Zhanlan Chen
, Jiangbin Zheng

软件学院

Northwestern Polytechnical University Xian

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

2 引用（Scopus）

摘要

Automatic pancreas segmentation from Computed Tomography (CT) images is a prerequisite of clinical practices such as cancer detection, yet challenging due to the variability in shape. To address this challenge, we propose a Hierarchical Convolutional Neural Network (H-CNN) to fuse multi-scale features, which could remedy the lost image details in progressive convolutional and pooling layers. In our proposed H-CNN, a hierarchical fusion block is designed to fuse low-level and high-level features across different layers. The H-CNN is evaluated on NIH pancreas dataset and outperforms the current state-of-art methods by achieving 86.59% ± 4.33% in terms of DSC. The experimental results confirm the effectiveness of the proposed H-CNN.

源语言	英语
主期刊名	Advances in Brain Inspired Cognitive Systems - 10th International Conference, BICS 2019, Proceedings
编辑	Jinchang Ren, Amir Hussain, Huimin Zhao, Jun Cai, Rongjun Chen, Yinyin Xiao, Kaizhu Huang, Jiangbin Zheng
出版商	Springer
页	406-413
页数	8
ISBN（印刷版）	9783030394301
DOI	https://doi.org/10.1007/978-3-030-39431-8_39
出版状态	已出版 - 2020
活动	10th International Conference on Brain Inspired Cognitive Systems, BICS 2019 - Guangzhou, 中国期限: 13 7月 2019 → 14 7月 2019

出版系列

姓名	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	11691 LNAI
ISSN（印刷版）	0302-9743
ISSN（电子版）	1611-3349

会议

会议	10th International Conference on Brain Inspired Cognitive Systems, BICS 2019
国家/地区	中国
市	Guangzhou
时期	13/07/19 → 14/07/19

联合国可持续发展目标

此成果有助于实现下列可持续发展目标：

可持续发展目标 3 良好健康与福祉

访问文件

10.1007/978-3-030-39431-8_39

其它文件与链接

链接到 Scopus 的出版物

引用此

Chen, Z., & Zheng, J. (2020). Deep neural network for pancreas segmentation from CT images. 在 J. Ren, A. Hussain, H. Zhao, J. Cai, R. Chen, Y. Xiao, K. Huang, & J. Zheng (编辑), Advances in Brain Inspired Cognitive Systems - 10th International Conference, BICS 2019, Proceedings (页码 406-413). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 11691 LNAI). Springer. https://doi.org/10.1007/978-3-030-39431-8_39

Chen, Zhanlan ; Zheng, Jiangbin. / Deep neural network for pancreas segmentation from CT images. Advances in Brain Inspired Cognitive Systems - 10th International Conference, BICS 2019, Proceedings. 编辑 / Jinchang Ren ; Amir Hussain ; Huimin Zhao ; Jun Cai ; Rongjun Chen ; Yinyin Xiao ; Kaizhu Huang ; Jiangbin Zheng. Springer, 2020. 页码 406-413 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{8eede67ec03b443eafbade4fa6de251e,

title = "Deep neural network for pancreas segmentation from CT images",

abstract = "Automatic pancreas segmentation from Computed Tomography (CT) images is a prerequisite of clinical practices such as cancer detection, yet challenging due to the variability in shape. To address this challenge, we propose a Hierarchical Convolutional Neural Network (H-CNN) to fuse multi-scale features, which could remedy the lost image details in progressive convolutional and pooling layers. In our proposed H-CNN, a hierarchical fusion block is designed to fuse low-level and high-level features across different layers. The H-CNN is evaluated on NIH pancreas dataset and outperforms the current state-of-art methods by achieving 86.59\% ± 4.33\% in terms of DSC. The experimental results confirm the effectiveness of the proposed H-CNN.",

keywords = "Convolutional Neural Network, Medical image segmentation, Pancreas segmentation",

author = "Zhanlan Chen and Jiangbin Zheng",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.; 10th International Conference on Brain Inspired Cognitive Systems, BICS 2019 ; Conference date: 13-07-2019 Through 14-07-2019",

year = "2020",

doi = "10.1007/978-3-030-39431-8\_39",

language = "英语",

isbn = "9783030394301",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "406--413",

editor = "Jinchang Ren and Amir Hussain and Huimin Zhao and Jun Cai and Rongjun Chen and Yinyin Xiao and Kaizhu Huang and Jiangbin Zheng",

booktitle = "Advances in Brain Inspired Cognitive Systems - 10th International Conference, BICS 2019, Proceedings",

}

Chen, Z & Zheng, J 2020, Deep neural network for pancreas segmentation from CT images. 在 J Ren, A Hussain, H Zhao, J Cai, R Chen, Y Xiao, K Huang & J Zheng (编辑), Advances in Brain Inspired Cognitive Systems - 10th International Conference, BICS 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 11691 LNAI, Springer, 页码 406-413, 10th International Conference on Brain Inspired Cognitive Systems, BICS 2019, Guangzhou, 中国, 13/07/19. https://doi.org/10.1007/978-3-030-39431-8_39

Deep neural network for pancreas segmentation from CT images. / Chen, Zhanlan; Zheng, Jiangbin.
Advances in Brain Inspired Cognitive Systems - 10th International Conference, BICS 2019, Proceedings. 编辑 / Jinchang Ren; Amir Hussain; Huimin Zhao; Jun Cai; Rongjun Chen; Yinyin Xiao; Kaizhu Huang; Jiangbin Zheng. Springer, 2020. 页码 406-413 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 11691 LNAI).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Deep neural network for pancreas segmentation from CT images

AU - Chen, Zhanlan

AU - Zheng, Jiangbin

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2020.

PY - 2020

Y1 - 2020

N2 - Automatic pancreas segmentation from Computed Tomography (CT) images is a prerequisite of clinical practices such as cancer detection, yet challenging due to the variability in shape. To address this challenge, we propose a Hierarchical Convolutional Neural Network (H-CNN) to fuse multi-scale features, which could remedy the lost image details in progressive convolutional and pooling layers. In our proposed H-CNN, a hierarchical fusion block is designed to fuse low-level and high-level features across different layers. The H-CNN is evaluated on NIH pancreas dataset and outperforms the current state-of-art methods by achieving 86.59% ± 4.33% in terms of DSC. The experimental results confirm the effectiveness of the proposed H-CNN.

AB - Automatic pancreas segmentation from Computed Tomography (CT) images is a prerequisite of clinical practices such as cancer detection, yet challenging due to the variability in shape. To address this challenge, we propose a Hierarchical Convolutional Neural Network (H-CNN) to fuse multi-scale features, which could remedy the lost image details in progressive convolutional and pooling layers. In our proposed H-CNN, a hierarchical fusion block is designed to fuse low-level and high-level features across different layers. The H-CNN is evaluated on NIH pancreas dataset and outperforms the current state-of-art methods by achieving 86.59% ± 4.33% in terms of DSC. The experimental results confirm the effectiveness of the proposed H-CNN.

KW - Convolutional Neural Network

KW - Medical image segmentation

KW - Pancreas segmentation

UR - https://www.scopus.com/pages/publications/85080956657

U2 - 10.1007/978-3-030-39431-8_39

DO - 10.1007/978-3-030-39431-8_39

M3 - 会议稿件

AN - SCOPUS:85080956657

SN - 9783030394301

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 406

EP - 413

BT - Advances in Brain Inspired Cognitive Systems - 10th International Conference, BICS 2019, Proceedings

A2 - Ren, Jinchang

A2 - Hussain, Amir

A2 - Zhao, Huimin

A2 - Cai, Jun

A2 - Chen, Rongjun

A2 - Xiao, Yinyin

A2 - Huang, Kaizhu

A2 - Zheng, Jiangbin

PB - Springer

T2 - 10th International Conference on Brain Inspired Cognitive Systems, BICS 2019

Y2 - 13 July 2019 through 14 July 2019

ER -

Chen Z, Zheng J. Deep neural network for pancreas segmentation from CT images. 在 Ren J, Hussain A, Zhao H, Cai J, Chen R, Xiao Y, Huang K, Zheng J, 编辑, Advances in Brain Inspired Cognitive Systems - 10th International Conference, BICS 2019, Proceedings. Springer. 2020. 页码 406-413. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-39431-8_39

Deep neural network for pancreas segmentation from CT images

摘要

出版系列

会议

联合国可持续发展目标

访问文件

其它文件与链接

指纹

引用此