Remember Me
Or use your Academic/Social account:


Or use your Academic/Social account:


You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.


Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message


Verify Password:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Magee, Derek; Tanner, Steven; Waller, Michael; McGonagle, Dennis; Jeavons, Alan (2005)
Publisher: Springer
Languages: English
Types: Part of book or chapter of book
A method for the non-rigid, multi-modal, registration of volumetric scans of human hands is presented. PET and MR scans are aligned by optimising the configuration of a tube based model using a set of Bayesian networks. Efficient optimisation is performed by posing the problem as a\ud multi-scale, local, discrete (quantised) search, and using dynamic programming. The method is to be used within a project to study the use of high-resolution HIDAC PET imagery in investigating bone growth and erosion in arthritis.\ud
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 1. Myers, R.: The application of PET-MR image registration in the brain. The British Journal of Radiology 75 (2002) 31-35
    • 2. Woods, R., Grafton, S., Holmes, C., Cherry, S., Mazziotta, J.: Automated image registration I. Journal of Computer Assisted Tomography 22(1) (1998) 139-152
    • 3. Wells, W., Viola, P., Atsumi, H., Nakajima, S., Kikinis, R.: Multi-modal volume registration by maximisation of mutual information. Medical Image Analysis 1(1) (1996) 35-51
    • 4. Studholme, C., Hill, D., Hawkes, D.: Automated 3D registration of magnetic resonance and positron emssion tomography brain images by multi-resolution optimization of voxel similarity measures. Medical Physics 24(1) (1997) 25-35
    • 5. West, J., Fitzpatrick, M., Wang, M., et al.: Comparison and evaluation of retrospective intermodality brain image registration techniques. Journal of Computer Assisted Tomography 21(4) (1997) 554-566
    • 6. Makela, T., Pham, Q., Clarysse, P., Neonen, J., Lotjonen, J., Sipila, O., Hanninen, H., Lauerma, K., Knuuti, J., Katila, T., Magnin, I.: A 3D model-based registration approach for the PET, MR and MCG cardiac data fusion. Medical Image Analysis 7(3) (2003) 377-389
    • 7. Farahani, K., Slates, R., Shao, Y., Silverman, R., Cherry, S.: Contemporaneous positron emission tomography and MR imaging at 1.5T. Journal of Magnetic Resonance Imaging 9 (1999) 497-500
    • 8. Hogg, D.: Model-based vision: A program to see a walking person. Image and Vision Computing 1 (1983) 5-20
    • 9. Rehg, J., Kanade, T.: Visual tracking of high DOF atriculated structures: An application to human hand tracking. In: Proc. European Conference on Computer Vision. (1994) 35-46
    • 10. Stenger, B., Mendonca, P., Cipolla, R.: Model-based hand tracking using an unscented kalman filter. In: Proc. British Machine Vision Conference. (2001) 53-72
    • 11. Felzenswalb, P., Huttenlocher, D.: Efficient matching of pictorial structures. In: Proc. IEEE Conf. on Computer Vision and Pattern Recognition. (2000)
    • 12. Horn, B.: Closed-form solution of absolute orientation using unit quaternions. Journal of the Optical Society of America 4(4) (1987) 629-642
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article