Hextuple registration of interim and follow-up PET-CT images for the accurate tracking of patient recovery after therapy

An extended registration framework is presented to accurately register follow-up PET-CT study triples. Since there are six images to register, sophisticated feature extraction and similarity measurement methods are proposed. An irregular sampling method is introduced to decrease the processing speed of the hextuple registration. The similarity measurement is based on a normalized hybrid extended SSD (Sum of Squared Differences) and and extended NMI (Normalized mutual Information). The method has been tested on a huge amount of simulated data to avoid observer specific results. Based on the validation, our method outperforms prior solutions in both speed and accuracy, hence it should be the subject of further investigations.

[1]  Martin Hutchings,et al.  FDG-PET after two cycles of chemotherapy predicts treatment failure and progression-free survival in Hodgkin lymphoma. , 2006, Blood.

[2]  Max A. Viergever,et al.  Mutual-information-based registration of medical images: a survey , 2003, IEEE Transactions on Medical Imaging.

[3]  Toshi Hiro Nishimura,et al.  Medical image noise reduction using Radon transform and Walsh list in Laplacian pyramid domain , 2009, 2009 IEEE 13th International Symposium on Consumer Electronics.

[4]  Polina Golland,et al.  Free-Form B-spline Deformation Model for Groupwise Registration. , 2007, Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention.

[5]  Pramod K. Varshney,et al.  Mutual information-based CT-MR brain image registration using generalized partial volume joint histogram estimation , 2003, IEEE Transactions on Medical Imaging.

[6]  Brian Hutton,et al.  A Multi-component similarity measure for improved robustness of non-rigid registration of combined FDG PET-CT head and neck images , 2009 .

[7]  James M Balter,et al.  Mutual information based CT registration of the lung at exhale and inhale breathing states using thin-plate splines. , 2004, Medical physics.

[8]  Nassir Navab,et al.  Structural image representation for image registration , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops.

[9]  Thomas Beyer,et al.  FDG-PET/CT in re-staging of patients with lymphoma , 2004, European Journal of Nuclear Medicine and Molecular Imaging.

[10]  E. Hoffman,et al.  Mass preserving nonrigid registration of CT lung images using cubic B-spline. , 2009, Medical physics.

[11]  Dominique Van de Sompel,et al.  Simultaneous reconstruction and registration algorithm for limited view transmission tomography using a multiple cluster approximation to the joint histogram with an anatomical prior , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[12]  Ronald R Price,et al.  FDG PET in the follow-up management of patients with newly diagnosed Hodgkin and non-Hodgkin lymphoma after first-line chemotherapy. , 2003, International journal of radiation oncology, biology, physics.

[13]  Ur Metser,et al.  Role of 18F-FDG PET/CT in Staging and Follow-up of Lymphoma in Pediatric and Young Adult Patients , 2006, Journal of computer assisted tomography.