Journal of Mathematical Imaging and Vision

, Volume 44, Issue 3, pp 463–479 | Cite as

Full Multiresolution Active Shape Models

  • Juan J. CerrolazaEmail author
  • Arantxa Villanueva
  • Federico M. Sukno
  • Constantine Butakoff
  • Alejandro F. Frangi
  • Rafael Cabeza


The incorporation of a multiresolution image approach is one of the most popular variants of Active Shape Models (ASMs), providing a more robust algorithm and minimizing its initialization dependency. Using the wavelet transform, the present paper extends the multiresolution analysis to the shape space, developing a novel multiresolution shape framework, capable of being incorporated into most of ASM variants. The tests performed with two different types of images, face images (AR database) and chest radiographs (JSRT database), demonstrate how this new generation of algorithms significantly reduce the computational cost, more than halving it, while maintaining the same levels of accuracy.


Active shape model Multiresolution analysis Medical image segmentation Wavelet transform 



The work described in this study was supported by the Spanish Ministry of Science and Innovation with an FPU grant (AP2007-03931). This work was also partially supported by the Spanish Ministry of Science and Innovation (Ref. TIN2009-14536-C02-01), Plan E and FEDER.


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Juan J. Cerrolaza
    • 1
    Email author
  • Arantxa Villanueva
    • 1
  • Federico M. Sukno
    • 3
    • 4
  • Constantine Butakoff
    • 2
  • Alejandro F. Frangi
    • 2
  • Rafael Cabeza
    • 1
  1. 1.Department of Electrical and Electronic EngineeringPublic University of NavarraPamplonaSpain
  2. 2.Research Group for Computational Imaging and Simulation Technologies in BiomedicineUniversitat Pompeu FabraBarcelonaSpain
  3. 3.Centre for Image Processing & AnalysisDublin City UniversityDublin 9Ireland
  4. 4.Molecular & Cellular TherapeuticsRoyal College of Surgeons in IrelandDublin 2Ireland

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