Papiez, Bartlomiej Wladyslaw (2012) Diffeomorphic image registration with applications to deformation modelling between multiple data sets. Doctoral thesis, University of Central Lancashire.
PDF (Thesis Document)
- Accepted Version
Available under License Creative Commons Attribution Non-commercial Share Alike.
Over last years, the diffeomorphic image registration algorithms have been successfully introduced into the field of the medical image analysis. At the same time, the particular usability of these techniques, in majority derived from the solid mathematical background, has been only quantitatively explored for the limited applications such as longitudinal studies on treatment quality, or diseases progression.
The thesis considers the deformable image registration algorithms, seeking out those that maintain the medical correctness of the estimated dense deformation fields in terms of the preservation of the object and its neighbourhood topology, offer the reasonable computational complexity to satisfy time restrictions coming from the potential applications, and are able to cope with low quality data typically encountered in Adaptive Radiotherapy (ART). The research has led to the main emphasis being laid on the diffeomorphic image registration to achieve one-to-one mapping between images. This involves introduction of the log-domain parameterisation of the deformation field by its approximation via a stationary velocity field.
A quantitative and qualitative examination of existing and newly proposed algorithms for pairwise deformable image registration presented in this thesis, shows that the log-Euclidean parameterisation can be successfully utilised in the biomedical applications. Although algorithms utilising the log-domain parameterisation have theoretical justification for maintaining diffeomorphism, in general, the deformation fields produced by them have similar properties as these estimated by classical methods. Having this in mind, the best compromise in terms of the quality of the deformation fields has been found for the consistent image registration framework. The experimental results suggest also that the image registration with the symmetrical warping of the input images outperforms the classical approaches, and simultaneously can be easily introduced to most known algorithms.
Furthermore, the log-domain implicit group-wise image registration is proposed. By linking the various sets of images related to the different subjects, the proposed image registration approach establishes a common subject space and between-subject correspondences therein. Although the correspondences between groups of images can be found by performing the classic image registration, the reference image selection (not required in the proposed implementation), may lead to a biased mean image being estimated and the corresponding common subject space not adequate to represent the general properties of the data sets.
The approaches to diffeomorphic image registration have been also utilised as the principal elements for estimating the movements of the organs in the pelvic area based on the dense deformation field prediction system driven by the partial information coming from the specific type of the measurements parameterised using the implicit surface representation, and recognising facial expressions where the stationary velocity fields are used as the facial expression descriptors. Both applications have been extensively evaluated based on the real representative data sets of three-dimensional volumes and two-dimensional images, and the obtained results indicate the practical usability of the proposed techniques.
|Item Type:||Thesis (Doctoral)|
|Additional Information:||Publications Bartlomiej W. Papież, Tomasz P. Zieliński, Bogdan J. Matuszewski, Deformable Image Registration - Improved Fast Free Form Deformation, VISAPP 2010 - Proceedings of the Fifth International Conference on Computer Vision Theory and Applications, Angers, France, May 17-21, 2010 - Volume1, pp 530-535. Bartlomiej W. Papież, Bogdan J. Matuszewski Direct inverse deformation field approach to pelvic-area symmetric image registration, MIUA 2011 - Proceedings of the 15th Conference on Medical Image Understanding and Analysis, London, UK, July 14-15, 2011, pp 193-197. Bartlomiej W. Papież, Bogdan J. Matuszewski, Lik-Kwan Shark, Wei Quan, Facial Expression Recognition using Log- Euclidean Statistical Shape Models, ICPRAM 2012 - Proceedings of the First International Conference on Pattern Recognition Applications and Methods, Vilamoura, Portugal, February 6-8, 2012, pp 351-359. Bartlomiej W. Papież, Bogdan J. Matuszewski, Symmetric image registration with directly calculated inverse deformation field, The Annals of the British Machine Vision Association, 2012(6), pp 1-14. Bartlomiej W. Papież, Bogdan J. Matuszewski, Lik-Kwan Shark, Christopher Moore, An implicit inter-subject shape driven image deformation model for prostate motion estimation, 4th MICCAI Workshop on Computational and Clinical Applications in Abdominal Imaging (CCAAI), Nice, France, October 1st, 2012, pp 218-228. Bartlomiej W. Papież, Bogdan J. Matuszewski, Lik-Kwan Shark, Wei Quan, Facial Expression Recognition using Diffeomorphic Image Registration Framework, Mathematical Methodologies in Pattern Recognition and Machine Learning - Contributions from the International Conference on Pattern Recognition Applications and Methods, Springer Proceedings in Mathematics&Statistics, 2012, in press, accepted manuscript|
|Uncontrolled Keywords (separate with ;):||Diffeomorphic; deformable image registration;|
|Subjects:||Computer science > Computer architectures & operating systems|
|Schools:||Faculty of Science and Technology > School of Physical Sciences and Computing|
|Deposited By:||Hayley Gayle Moran|
|Deposited On:||01 Aug 2013 10:32|
|Last Modified:||10 Feb 2017 12:42|
Downloads per month over past year
Downloads for past 30 days
Repository Staff Only: item control page