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research-article

Computer Aided Annotation of Early Esophageal Cancer in Gastroscopic Images based on Deeplabv3+ Network

Authors:

Hong Xiu Jiang,

Tao GanAuthors Info & Claims

ICBIP '19: Proceedings of the 4th International Conference on Biomedical Signal and Image Processing

Pages 56 - 61

https://doi.org/10.1145/3354031.3354046

Published: 13 August 2019 Publication History

Abstract

The diagnoses of Early Esophageal Cancer (EEC) based on gastroscopic images is a challenging task in clinic, which relies heavily on subjective artificial detection and annotation. As a result, computer aided diagnosis (CAD) methods that support the clinicians become highly attractive. In this paper, we proposed a CAD method which realized the automatic detection and annotation of EEC lesions in gastroscopic images. The proposed method initially utilized an advanced Deep Learning (DL) network Deeplabv3+ to obtain a preliminary prediction of EEC regions. Then, a post-processing step which referenced the clinical requirements was designed and applied to get the final annotation results. Totally 3190 gastroscopic images of 732 patients were used in this work. The final experimental results show that the EEC detection rate of our method was 97.07%, and the mean Dice Similarity Coefficient (DSC) was 74.01%, which are higher than those of other state-of-the-are DL-based methods. In addition, the false positive output of our method is fewer. Therefore, the proposed method offers a good potential to aid the clinical diagnoses of EEC.

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https://doi.org/10.1109/ACCESS.2023.3313390
Chempak Kumar AMuhammad Noorul Mubarak D(2023)Classification of Esophageal Cancer Using Ensembled CNN with Generalized Normal Distribution Optimization Model and Support Vector Machine ClassifierCongress on Smart Computing Technologies10.1007/978-981-99-2468-4_8(83-111)Online publication date: 11-Jul-2023
https://doi.org/10.1007/978-981-99-2468-4_8
Pan XDai DWang HLiu XBai W(2022)Nasopharyngeal Organ Segmentation Algorithm Based on Dilated Convolution Feature PyramidThe International Conference on Image, Vision and Intelligent Systems (ICIVIS 2021)10.1007/978-981-16-6963-7_4(45-58)Online publication date: 3-Mar-2022
https://doi.org/10.1007/978-981-16-6963-7_4
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Index Terms

Computer Aided Annotation of Early Esophageal Cancer in Gastroscopic Images based on Deeplabv3+ Network
1. Applied computing
  1. Life and medical sciences
    1. Computational biology
      1. Imaging
2. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Image segmentation

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ICBIP '19: Proceedings of the 4th International Conference on Biomedical Signal and Image Processing

August 2019

149 pages

ISBN:9781450372244

DOI:10.1145/3354031

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Graduate School of Library, Information, and Media Studies, University of Tsukuba, Japan: Graduate School of Library, Information, and Media Studies, University of Tsukuba, Japan
Sichuan University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 August 2019

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National Natural Science Foundation of China
Key project of Natural Science Foundation of Guangdong province
Sichuan Province Science and Technology Support Program

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ICBIP '19

ICBIP '19: 2019 4th International Conference on Biomedical Signal and Image Processing

August 13 - 15, 2019

Chengdu, China

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Cited By

Wang RCai MXia Z(2023)A Lightweight High-Resolution RS Image Road Extraction Method Combining Multi-Scale and Attention MechanismIEEE Access10.1109/ACCESS.2023.331339011(108956-108966)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3313390
Chempak Kumar AMuhammad Noorul Mubarak D(2023)Classification of Esophageal Cancer Using Ensembled CNN with Generalized Normal Distribution Optimization Model and Support Vector Machine ClassifierCongress on Smart Computing Technologies10.1007/978-981-99-2468-4_8(83-111)Online publication date: 11-Jul-2023
https://doi.org/10.1007/978-981-99-2468-4_8
Pan XDai DWang HLiu XBai W(2022)Nasopharyngeal Organ Segmentation Algorithm Based on Dilated Convolution Feature PyramidThe International Conference on Image, Vision and Intelligent Systems (ICIVIS 2021)10.1007/978-981-16-6963-7_4(45-58)Online publication date: 3-Mar-2022
https://doi.org/10.1007/978-981-16-6963-7_4
Kundu AFattah SWahid K(2020)Multiple Linear Discriminant Models for Extracting Salient Characteristic Patterns in Capsule Endoscopy Images for Multi-Disease DetectionIEEE Journal of Translational Engineering in Health and Medicine10.1109/JTEHM.2020.29646668(1-11)Online publication date: 2020
https://doi.org/10.1109/JTEHM.2020.2964666
Syed TDoshi AGuleria SSyed SShah T(2020)Artificial Intelligence and Its Role in Identifying Esophageal NeoplasiaDigestive Diseases and Sciences10.1007/s10620-020-06643-265:12(3448-3455)Online publication date: 15-Oct-2020
https://doi.org/10.1007/s10620-020-06643-2

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