Constraints on deformable models: recovering 3D shape and nongrid motion
Artificial Intelligence
On active contour models and balloons
CVGIP: Image Understanding
Region-based strategies for active contour models
International Journal of Computer Vision
Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalized gradient vector flow external forces for active contours
Signal Processing - Special issue on deformable models and techniques for image and signal processing
A Level Set Model for Image Classification
International Journal of Computer Vision
General Scheme of Region Competition Based on Scale Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geodesic Active Regions and Level Set Methods for Supervised Texture Segmentation
International Journal of Computer Vision
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear Shape Statistics in Mumford-Shah Based Segmentation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Fuzzy Markovian segmentation in application of magnetic resonance images
Computer Vision and Image Understanding
Image segmentation by reaction-diffusion bubbles
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Geometric models for active contours
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 3)-Volume 3 - Volume 3
A Variational Framework for Joint Segmentation and Registration
MMBIA '01 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA'01)
Information-Theoretic Active Polygons for Unsupervised Texture Segmentation
International Journal of Computer Vision
Fast 3d brain segmentation using dual-front active contours with optional user-interaction
CVBIA'05 Proceedings of the First international conference on Computer Vision for Biomedical Image Applications
A generalized divergence measure for robust image registration
IEEE Transactions on Signal Processing
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Fast incorporation of optical flow into active polygons
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Human activity modeling as brownian motion on shape manifold
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Human activity modeling on shape manifold
EG 3DOR'11 Proceedings of the 4th Eurographics conference on 3D Object Retrieval
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We propose a constrained version of Mumford and Shah's (1989) segmentation model with an information-theoretic point of view in order to devise a systematic procedure to segment brain magnetic resonance imaging (MRI) data for parametric T1-Map and T1-weighted images, in both 2-D and 3D settings. Incorporation of a tuning weight in particular adds a probabilistic flavor to our segmentation method, and makes the 3-tissue segmentation possible. Moreover, we proposed a novel method to jointly segment the T1-Map and calibrate RF Inhomogeneity (JSRIC). This method assumes the average T1 value of white matter is the same across transverse slices in the central brain region, and JSRIC is able to rectify the flip angles to generate calibrated T1-Maps. In order to generate an accurate T1-Map, the determination of optimal flip-angles and the registration of flip-angle images are examined. Our JSRIC method is validated on two human subjects in the 2D T1-Map modality and our segmentation method is validated by two public databases, BrainWeb and IBSR, of T1-weighted modality in the 3D setting.