IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v196y2012i1p737-76510.1007-s10479-010-0760-8.html
   My bibliography  Save this article

Discrete and geometric Branch and Bound algorithms for medical image registration

Author

Listed:

Abstract

Aiming at the development of an exact solution method for registration problems, we present two different Branch & Bound algorithms for a mixed integer programming formulation of the problem. The first B&B algorithm branches on binary assignment variables and makes use of an optimality condition that is derived from a graph matching formulation. The second, geometric B&B algorithm applies a geometric branching strategy on continuous transformation variables. The two approaches are compared for synthetic test examples as well as for 2-dimensional medical data. The results show that medium sized problem instances can be solved to global optimality in a reasonable amount of time. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Frank Pfeuffer & Michael Stiglmayr & Kathrin Klamroth, 2012. "Discrete and geometric Branch and Bound algorithms for medical image registration," Annals of Operations Research, Springer, vol. 196(1), pages 737-765, July.
  • Handle: RePEc:spr:annopr:v:196:y:2012:i:1:p:737-765:10.1007/s10479-010-0760-8
    DOI: 10.1007/s10479-010-0760-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-010-0760-8
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10479-010-0760-8?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. Loiola, Eliane Maria & de Abreu, Nair Maria Maia & Boaventura-Netto, Paulo Oswaldo & Hahn, Peter & Querido, Tania, 2007. "A survey for the quadratic assignment problem," European Journal of Operational Research, Elsevier, vol. 176(2), pages 657-690, January.
    2. Jochen Gorski & Frank Pfeuffer & Kathrin Klamroth, 2007. "Biconvex sets and optimization with biconvex functions: a survey and extensions," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 66(3), pages 373-407, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ha Che-Ngoc & Thao Nguyen-Trang & Tran Nguyen-Bao & Trung Nguyen-Thoi & Tai Vo-Van, 2022. "A new approach for face detection using the maximum function of probability density functions," Annals of Operations Research, Springer, vol. 312(1), pages 99-119, May.
    2. Li, Yifu & Qi, Xiangtong, 2022. "A geometric branch-and-bound algorithm for the service bundle design problem," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1044-1056.
    3. Gang Kou & Wenshuai Wu, 2014. "Multi-criteria decision analysis for emergency medical service assessment," Annals of Operations Research, Springer, vol. 223(1), pages 239-254, December.

    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. Lin, Yun Hui & Wang, Yuan & He, Dongdong & Lee, Loo Hay, 2020. "Last-mile delivery: Optimal locker location under multinomial logit choice model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    2. Yunpeng Sun & Ruoya Jia & Asif Razzaq & Qun Bao, 2023. "Drivers of China’s geographical renewable energy development: evidence from spatial association network structure approaches," Economic Change and Restructuring, Springer, vol. 56(6), pages 4115-4163, December.
    3. Herrán, Alberto & Manuel Colmenar, J. & Duarte, Abraham, 2021. "An efficient variable neighborhood search for the Space-Free Multi-Row Facility Layout problem," European Journal of Operational Research, Elsevier, vol. 295(3), pages 893-907.
    4. Ma, Shujie & Linton, Oliver & Gao, Jiti, 2021. "Estimation and inference in semiparametric quantile factor models," Journal of Econometrics, Elsevier, vol. 222(1), pages 295-323.
    5. Ricardo M. Lima & Ignacio E. Grossmann, 2017. "On the solution of nonconvex cardinality Boolean quadratic programming problems: a computational study," Computational Optimization and Applications, Springer, vol. 66(1), pages 1-37, January.
    6. Michela Ricciardi Celsi & Lorenzo Ricciardi Celsi, 2024. "Quantum Computing as a Game Changer on the Path towards a Net-Zero Economy: A Review of the Main Challenges in the Energy Domain," Energies, MDPI, vol. 17(5), pages 1-22, February.
    7. Krešimir Mihić & Kevin Ryan & Alan Wood, 2018. "Randomized Decomposition Solver with the Quadratic Assignment Problem as a Case Study," INFORMS Journal on Computing, INFORMS, vol. 30(2), pages 295-308, May.
    8. Papahristodoulou, Christos, 2009. "The optimal layout of football players: A case study for AC Milan," MPRA Paper 20102, University Library of Munich, Germany.
    9. Alistair Wilson & Mariagiovanna Baccara & Ayse Imrohoroglu & Leeat Yariv, 2009. "A Field Study on Matching with Network Externalities," Working Paper 486, Department of Economics, University of Pittsburgh, revised Sep 2011.
    10. Mishra, Aditya & Dey, Dipak K. & Chen, Yong & Chen, Kun, 2021. "Generalized co-sparse factor regression," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
    11. Jia, Zhao-hong & Li, Kai & Leung, Joseph Y.-T., 2015. "Effective heuristic for makespan minimization in parallel batch machines with non-identical capacities," International Journal of Production Economics, Elsevier, vol. 169(C), pages 1-10.
    12. Shen, Yuelin, 2018. "Pricing contracts and planning stochastic resources in brand display advertising," Omega, Elsevier, vol. 81(C), pages 183-194.
    13. Blanco, Víctor & Fernández, Elena & Puerto, Justo, 2017. "Minimum Spanning Trees with neighborhoods: Mathematical programming formulations and solution methods," European Journal of Operational Research, Elsevier, vol. 262(3), pages 863-878.
    14. Pessoa, Artur Alves & Hahn, Peter M. & Guignard, Monique & Zhu, Yi-Rong, 2010. "Algorithms for the generalized quadratic assignment problem combining Lagrangean decomposition and the Reformulation-Linearization Technique," European Journal of Operational Research, Elsevier, vol. 206(1), pages 54-63, October.
    15. Angel Juan & Javier Faulin & Albert Ferrer & Helena Lourenço & Barry Barrios, 2013. "MIRHA: multi-start biased randomization of heuristics with adaptive local search for solving non-smooth routing problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(1), pages 109-132, April.
    16. Zhiqing Meng & Min Jiang & Rui Shen & Leiyan Xu & Chuangyin Dang, 2021. "An objective penalty function method for biconvex programming," Journal of Global Optimization, Springer, vol. 81(3), pages 599-620, November.
    17. Keller, Birgit & Buscher, Udo, 2015. "Single row layout models," European Journal of Operational Research, Elsevier, vol. 245(3), pages 629-644.
    18. Mădălina M. Drugan, 2015. "Generating QAP instances with known optimum solution and additively decomposable cost function," Journal of Combinatorial Optimization, Springer, vol. 30(4), pages 1138-1172, November.
    19. Huizhen Zhang & Cesar Beltran-Royo & Liang Ma, 2013. "Solving the quadratic assignment problem by means of general purpose mixed integer linear programming solvers," Annals of Operations Research, Springer, vol. 207(1), pages 261-278, August.
    20. Dimitris Bertsimas & Xuan Vinh Doan & Karthik Natarajan & Chung-Piaw Teo, 2010. "Models for Minimax Stochastic Linear Optimization Problems with Risk Aversion," Mathematics of Operations Research, INFORMS, vol. 35(3), pages 580-602, August.

    More about this item

    Statistics

    Access and download statistics

    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:annopr:v:196:y:2012:i:1:p:737-765:10.1007/s10479-010-0760-8. 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.