Deformation analysis to detect and quantify active lesions in three-dimensional medical image sequences
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[1] J S YOUNG,et al. The invasive growth of malignant tumours: an experimental interpretation based on elastic-jelly models. , 1959, The Journal of pathology and bacteriology.
[2] Robert C. Bolles,et al. Parametric Correspondence and Chamfer Matching: Two New Techniques for Image Matching , 1977, IJCAI.
[3] D. Burr. A dynamic model for image registration , 1981 .
[4] Guido Gerig,et al. Medical Imaging and Computer Vision: An Integrated Approach for Diagnosis and Planning , 1989, DAGM-Symposium.
[5] R. Kikinis,et al. Three-dimensional segmentation of MR images of the head using probability and connectivity. , 1990, Journal of computer assisted tomography.
[6] Laurent D. Cohen,et al. Using Deformable Surfaces to Segment 3-D Images and Infer Differential Structures , 1992, ECCV.
[7] C J Wallace,et al. Multiple sclerosis: the impact of MR imaging. , 1992, AJR. American journal of roentgenology.
[8] Xavier Pennec,et al. A Framework for Uncertainty and Validation of 3-D Registration Methods Based on Points and Frames , 1995, Proceedings of IEEE International Conference on Computer Vision.
[9] Heinz Handels,et al. Characterisation and Classification of Brain Tumours in Three-Dimensional MR Image Sequences , 1996, VBC.
[10] Guido Gerig,et al. Exploring the Discrimination Power of the Time Domain for Segmentation and Characterization of Lesions in Serial MR Data , 1998, MICCAI.
[11] Christos Davatzikos,et al. A Biomechanical Model of Soft Tissue Deformation, with Applications to Non-rigid Registration of Brain Images with Tumor Pathology , 1998, MICCAI.
[12] Jean-Philippe Thirion,et al. Image matching as a diffusion process: an analogy with Maxwell's demons , 1998, Medical Image Anal..
[13] R. Kikinis,et al. Quantitative follow‐up of patients with multiple sclerosis using MRI: Technical aspects , 1999, Journal of magnetic resonance imaging : JMRI.