research-article

Genetic programming for tuberculosis screening from raw X-ray images

Authors:

Armand R. Burks,

William F. PunchAuthors Info & Claims

GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference

Pages 1214 - 1221

https://doi.org/10.1145/3205455.3205461

Published: 02 July 2018 Publication History

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Abstract

Genetic programming has been successfully applied to several real-world problem domains. One such application area is image classification, wherein genetic programming has been used for a variety of problems such as breast cancer detection, face detection, and pedestrian detection, to name a few. We present the use of genetic programming for detecting active tuberculosis in raw X-ray images. Our results demonstrate that genetic programming evolves classifiers that achieve promising accuracy results compared to that of traditional image classification techniques. Our classifiers do not require pre-processing, segmentation, or feature extraction beforehand. Furthermore, our evolved classifiers process a raw X-ray image and return a classification orders of magnitude faster than the reported times for traditional techniques.

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Cited By

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Allison E(2024)Binary Classification of Medical Images by Symbolic RegressionAdvances in Computational Intelligence Systems10.1007/978-3-031-47508-5_40(516-527)Online publication date: 1-Feb-2024
https://doi.org/10.1007/978-3-031-47508-5_40
Bi YXue BMesejo PCagnoni SZhang M(2023)A Survey on Evolutionary Computation for Computer Vision and Image Analysis: Past, Present, and Future TrendsIEEE Transactions on Evolutionary Computation10.1109/TEVC.2022.322074727:1(5-25)Online publication date: Feb-2023
https://doi.org/10.1109/TEVC.2022.3220747
Jiang DTan CPeng JChen CWu XZhao WSong YTong YLiu CXu QYang QDeng L(2021)A GDPR-compliant Ecosystem for Speech Recognition with Transfer, Federated, and Evolutionary LearningACM Transactions on Intelligent Systems and Technology10.1145/344768712:3(1-19)Online publication date: 5-May-2021
https://dl.acm.org/doi/10.1145/3447687
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Index Terms

Genetic programming for tuberculosis screening from raw X-ray images
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Object detection
  2. Machine learning
    1. Machine learning approaches
      1. Bio-inspired approaches
        Genetic programming
      2. Classification and regression trees

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Information & Contributors

Information

Published In

GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference

July 2018

1578 pages

ISBN:9781450356183

DOI:10.1145/3205455

Editor:
Hernan Aguirre
Shinshu University
,
General Chair:
Keiki Takadama
The University of Electro-Communications

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 July 2018

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GECCO '18

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SIGEVO

GECCO '18: Genetic and Evolutionary Computation Conference

July 15 - 19, 2018

Kyoto, Japan

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

View all

Allison E(2024)Binary Classification of Medical Images by Symbolic RegressionAdvances in Computational Intelligence Systems10.1007/978-3-031-47508-5_40(516-527)Online publication date: 1-Feb-2024
https://doi.org/10.1007/978-3-031-47508-5_40
Bi YXue BMesejo PCagnoni SZhang M(2023)A Survey on Evolutionary Computation for Computer Vision and Image Analysis: Past, Present, and Future TrendsIEEE Transactions on Evolutionary Computation10.1109/TEVC.2022.322074727:1(5-25)Online publication date: Feb-2023
https://doi.org/10.1109/TEVC.2022.3220747
Jiang DTan CPeng JChen CWu XZhao WSong YTong YLiu CXu QYang QDeng L(2021)A GDPR-compliant Ecosystem for Speech Recognition with Transfer, Federated, and Evolutionary LearningACM Transactions on Intelligent Systems and Technology10.1145/344768712:3(1-19)Online publication date: 5-May-2021
https://dl.acm.org/doi/10.1145/3447687
Khan AQureshi AWahab NHussain MHamza M(2021)A recent survey on the applications of genetic programming in image processingComputational Intelligence10.1111/coin.1245937:4(1745-1778)Online publication date: Jun-2021
https://doi.org/10.1111/coin.12459
Bi YXue BZhang M(2021)Genetic Programming With Image-Related Operators and a Flexible Program Structure for Feature Learning in Image ClassificationIEEE Transactions on Evolutionary Computation10.1109/TEVC.2020.300222925:1(87-101)Online publication date: Feb-2021
https://doi.org/10.1109/TEVC.2020.3002229
Castellanos-Garzón JMezquita Martín YJaimes Sánchez JLópez García SCosta E(2020)A Genetic Programming Strategy to Induce Logical Rules for Clinical Data AnalysisProcesses10.3390/pr81215658:12(1565)Online publication date: 27-Nov-2020
https://doi.org/10.3390/pr8121565

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