IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/v42y2021i4d10.1007_s10878-019-00453-7.html
   My bibliography  Save this article

An improved linear convergence of FISTA for the LASSO problem with application to CT image reconstruction

Author

Listed:
  • Qian Li

    (Shanghai University Of Engineering Science)

  • Wei Zhang

    (National University of Singapore)

Abstract

The LASSO problem has been explored extensively for CT image reconstruction, the most useful algorithm to solve the LASSO problem is the FISTA. In this paper, we prove that FISTA has a better linear convergence rate than ISTA. Besides, we observe that the convergence rate of FISTA is closely related to the acceleration parameters used in the algorithm. Based on this finding, an acceleration parameter setting strategy is proposed. Moreover, we adopt the function restart scheme on FISTA to reconstruct CT images. A series of numerical experiments is carried out to show the superiority of FISTA over ISTA on signal processing and CT image reconstruction. The numerical experiments consistently demonstrate our theoretical results.

Suggested Citation

  • Qian Li & Wei Zhang, 2021. "An improved linear convergence of FISTA for the LASSO problem with application to CT image reconstruction," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 831-847, November.
    • Handle: RePEc:spr:jcomop:v:42:y:2021:i:4:d:10.1007_s10878-019-00453-7
    DOI: 10.1007/s10878-019-00453-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-019-00453-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10878-019-00453-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jian Chang & Lingjuan Zhang, 2019. "Case Mix Index weighted multi-objective optimization of inpatient bed allocation in general hospital," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 1-19, January.
    2. Ling Gai & Jiandong Ji, 2019. "An integrated method to solve the healthcare facility layout problem under area constraints," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 95-113, January.
    3. Liwei Zhong & Yanqin Bai, 2019. "Three-sided stable matching problem with two of them as cooperative partners," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 286-292, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qian Li & Wei Zhang, 0. "An improved linear convergence of FISTA for the LASSO problem with application to CT image reconstruction," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-17.
    2. Xuerui Gao & Yanqin Bai & Qian Li, 2021. "A sparse optimization problem with hybrid $$L_2{\text {-}}L_p$$ L 2 - L p regularization for application of magnetic resonance brain images," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 760-784, November.
    3. Xuanzhu Fan & Jiafu Tang & Chongjun Yan & Hainan Guo & Zhongfa Cao, 2021. "Outpatient appointment scheduling problem considering patient selection behavior: data modeling and simulation optimization," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 677-699, November.
    4. Xuerui Gao & Yanqin Bai & Qian Li, 0. "A sparse optimization problem with hybrid $$L_2{\text {-}}L_p$$L2-Lp regularization for application of magnetic resonance brain images," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-25.
    5. Xuanzhu Fan & Jiafu Tang & Chongjun Yan & Hainan Guo & Zhongfa Cao, 0. "Outpatient appointment scheduling problem considering patient selection behavior: data modeling and simulation optimization," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-23.
    6. He Huang & Wei Gao & Chunming Ye, 2021. "An intelligent data-driven model for disease diagnosis based on machine learning theory," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 884-895, November.
    7. Ruiping Wang & Mei Wang & Jian Chang & Zai Luo & Feng Zhang & Chen Huang, 2021. "An optimized approach of venous thrombus embolism risk assessment," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 1053-1063, November.
    8. Ruiping Wang & Mei Wang & Jian Chang & Zai Luo & Feng Zhang & Chen Huang, 0. "An optimized approach of venous thrombus embolism risk assessment," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-11.
    9. He Huang & Wei Gao & Chunming Ye, 0. "An intelligent data-driven model for disease diagnosis based on machine learning theory," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-12.
    10. Zhiguo Wang & Lufei Huang & Cici Xiao He, 2021. "A multi-objective and multi-period optimization model for urban healthcare waste’s reverse logistics network design," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 785-812, November.
    11. Jing Fan & Hui Shi, 0. "A three-stage supply chain scheduling problem based on the nursing assistants’ daily work in a hospital," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-13.
    12. Zhiguo Wang & Lufei Huang & Cici Xiao He, 0. "A multi-objective and multi-period optimization model for urban healthcare waste’s reverse logistics network design," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-28.
    13. Feng Zhang & Liwei Zhong, 0. "Three-sided matching problem with mixed preferences," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-9.
    14. Ling Gai & Zhiyue Peng & Jiming Zhang & Jiafu Zhang, 0. "Emergency medical center location problem with people evacuation solved by extended TODIM and objective programming," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-26.
    15. Feng Zhang & Liwei Zhong, 2021. "Three-sided matching problem with mixed preferences," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 928-936, November.
    16. Jing Fan & Hui Shi, 2021. "A three-stage supply chain scheduling problem based on the nursing assistants’ daily work in a hospital," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 896-908, November.
    17. Jorge Arenas & Juan Pablo Torres-Martínez, 2023. "Reconsidering the existence of stable solutions in three-sided matching problems with mixed preferences," Journal of Combinatorial Optimization, Springer, vol. 45(2), pages 1-8, March.
    18. Ling Gai & Zhiyue Peng & Jiming Zhang & Jiafu Zhang, 2021. "Emergency medical center location problem with people evacuation solved by extended TODIM and objective programming," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 1004-1029, November.
    19. Jorge Arenas & Juan Pablo Torres-Martinez, 2024. "On Incentives in Three-Sided Markets," Working Papers wp558, University of Chile, Department of Economics.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jcomop:v:42:y:2021:i:4:d:10.1007_s10878-019-00453-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.