A novel registration method based on coevolutionary strategy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Automatic registration is an important task to prepare aligned 2D images for 3D structure visualization, and it is a challenging problem especially for the microscope images. This paper proposes a novel coevolution-based coarse-to-fine registration method, aiming to align the regions of interest (ROIs) in the image sequence. Firstly, a coarse registration for whole images is executed by a scale-invariant feature transform (SIFT) based method, which can facilitate the segmentation of ROIs. Secondly, a fine registration for the segmented ROIs is done by a genetic algorithm (GA) with a novel coevolutionary strategy. Experimental results demonstrate the good performance of the proposed method and it is also successfully applied to the renal biopsy image sequence.

Original languageEnglish
Title of host publication2016 IEEE Congress on Evolutionary Computation, CEC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2375-2380
Number of pages6
ISBN (Electronic)9781509006229
DOIs
Publication statusPublished - 2016 Nov 14
Event2016 IEEE Congress on Evolutionary Computation, CEC 2016 - Vancouver, Canada
Duration: 2016 Jul 242016 Jul 29

Other

Other2016 IEEE Congress on Evolutionary Computation, CEC 2016
CountryCanada
CityVancouver
Period16/7/2416/7/29

ASJC Scopus subject areas

  • Artificial Intelligence
  • Modelling and Simulation
  • Computer Science Applications
  • Control and Optimization

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  • Cite this

    Zhang, J., & Furuzuki, T. (2016). A novel registration method based on coevolutionary strategy. In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 2375-2380). [7744082] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2016.7744082