1 / 27

Binary Tomography

17 th Summer School on Image Processing Debrecen, Hungary 2009. Binary Tomography. Introduction. Basic idea Computerized tomography Discrete tomography Binary tomography Applications. Problem description. Projections. Reconstruction. Known algorithms. Simulated annealing

Télécharger la présentation

Binary Tomography

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. 17th Summer School on Image Processing Debrecen, Hungary 2009 BinaryTomography

  2. Introduction • Basic idea • Computerized tomography • Discrete tomography • Binary tomography • Applications

  3. Problem description Projections Reconstruction

  4. Known algorithms • Simulated annealing • Linear relaxation • Branch and bound • SPG based method • Maximum flow problem • Neural networks • Convex-concave regularization • ...

  5. Our solutions • Simple solution • Star section algorithm for 2 and 4 projections • Evolutionary algorithm for 2D and 3D objects • Modified Kaczmarz algorithm

  6. Simple solution • Greedy algorithm Orginal image Reconstructions

  7. Star section algorithm • Maximum value of projections • Cross shape growing

  8. 2 projections - results

  9. 2 projections - results

  10. 2 projections - results

  11. 4 projections - results

  12. 4 projections - results

  13. 4 projections - results

  14. 4 projections - results

  15. Evolutionary algorithm for 2D • Population • Mutation • Crossover • Fitness • Prototype based representation of shapes

  16. 2D results 25% noise 10% noise Noisless

  17. 2D results

  18. Evolutionary algorithm for 3D

  19. Modified Kaczmarz algorithm • Linear system • r(i) is chosen from the set {1,2,...,m} at random, with probability proportional to

  20. Results

  21. Results

  22. Results

  23. Results

  24. Summary

  25. The avenue of future researches • Star section algorithm • Using circular directed growing instead of sectional • 3D implementation • Evolutionary algorithm • Automatic parameter adjustment • Applying algorithm to other shapes • Randomize Kaczmarz algorithm • Improving boundary reconstruction method

  26. A - team

  27. Thank You for Your Patiance

More Related