Principal Warps: Thin-Plate Splines and the Decomposition of Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image warping by radial basis functions: applications to facial expressions
CVGIP: Graphical Models and Image Processing
Computational methods in physics and engineering (2nd ed.)
Computational methods in physics and engineering (2nd ed.)
Warping and morphing of graphical objects
Warping and morphing of graphical objects
VRAIS '96 Proceedings of the 1996 Virtual Reality Annual International Symposium (VRAIS 96)
Intermodality registration and fusion of liver images for medical diagnosis
IIS '97 Proceedings of the 1997 IASTED International Conference on Intelligent Information Systems (IIS '97)
Synthesis of an Individualized Cranial Atlas with Dysmorphic Shape
MMBIA '96 Proceedings of the 1996 Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA '96)
Texture based medical image indexing and retrieval: application to cardiac imaging
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Medical Image Retrieval and Registration: Towards Computer Assisted Diagnostic Approach
IDEAS-DH '04 Proceedings of the IDEAS Workshop on Medical Information Systems: The Digital Hospital
Towards applying content-based image retrieval in the clinical routine
Future Generation Computer Systems
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In medical image registration and content-based image retrieval, the rigid transformation model is not adequate for anatomical structures that are elastic or deformable. For human structures such as abdomen, registration would involve global features such as abdominal wall as well as local target organs such as liver or spleen. A general non-rigid registration may not be sufficient to produce image matching of both global and local structures. In this study, a warping-deformable model is proposed to register images of such structures. This model uses a two-stage strategy for image registration of abdomen. In the first stage, the global-deformable transformation is used to register the global wall. The warping-transformation is used in second stage to register the liver. There is a good match of images using the proposed method (mean similarity index驴=驴0.73545).The image matching correlation coefficients calculated from eight pairs of CT and MR images of abdomen indicates that the warping-deformable transformation gives better matching of images than those without transformation (p驴t-test). This study has established a model for image registration of deformable structures. This is particularly important for data mining of image content retrieval for structures which are non-rigid. The result obtained is very promising but further clinical evaluation is needed