Medical image analysis
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Defining myocardial contours is often the most time-consuming portion of dynamic cardiac MRI image analysis. Displacement encoding with stimulated echoes (DENSE) is a quantitative MRI technique that encodes tissue displacement into the phase of the complex MRI images. Cine DENSE provides a time series of these images, thus facilitating the non-invasive study of myocardial kinematics. ⋯ In addition, a radial segmentation error metric was introduced for short-axis data. The average radial epicardial segmentation error was 0.36+/-0.08 and 0.40+/-0.10 pixels for slice-followed and conventional cine DENSE, respectively, and the average radial endocardial segmentation error was 0.46+/-0.12 and 0.46+/-0.16 pixels for slice following and conventional cine DENSE, respectively. Motion-guided segmentation employs the displacement-encoded phase shifts intrinsic to DENSE MRI to accurately propagate a single set of pre-defined contours throughout the remaining cardiac phases.
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Medical image analysis · Dec 2008
Groupwise surface correspondence by optimization: representation and regularization.
Groupwise optimization of correspondence across a set of unlabelled examples of shapes or images is a well-established technique that has been shown to produce quantitatively better models than other approaches. However, the computational cost of the optimization is high, leading to long convergence times. In this paper, we show how topologically non-trivial shapes can be mapped to regular grids, hence represented in terms of vector-valued functions defined on these grids (the shape image representation). ⋯ We also consider the question of regularization, and show that by borrowing ideas from image registration, it is possible to build a non-parametric, fluid regularizer for shapes, without losing the computational gain made by the use of shape images. We show that this non-parametric regularization leads to a further considerable gain, when compared to parametric regularization methods. Quantitative evaluation is performed on biological datasets, and shown to yield a substantial decrease in convergence time, with no loss of model quality.
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Medical image analysis · Dec 2008
Unifying framework for multimodal brain MRI segmentation based on Hidden Markov Chains.
In the frame of 3D medical imaging, accurate segmentation of multimodal brain MR images is of interest for many brain disorders. However, due to several factors such as noise, imaging artifacts, intrinsic tissue variation and partial volume effects, tissue classification remains a challenging task. In this paper, we present a unifying framework for unsupervised segmentation of multimodal brain MR images including partial volume effect, bias field correction, and information given by a probabilistic atlas. ⋯ This atlas is considered as a complementary sensor and the proposed method is extended to multimodal brain MRI without any user-tunable parameter (unsupervised algorithm). To validate this new unifying framework, we present experimental results on both synthetic and real brain images, for which the ground truth is available. Comparison with other often used techniques demonstrates the accuracy and the robustness of this new Markovian segmentation scheme.
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Medical image analysis · Apr 2008
Validation of a new surgical procedure for percutaneous scaphoid fixation using intra-operative ultrasound.
A new technique for percutaneous fixation of non-displaced scaphoid fractures is described. The technique used pre-operative planning from computed tomography images, registration to intra-operatively acquired three-dimensional ultrasound images, and intra-operative guidance using an optical tracking system. ⋯ Laboratory validation of the technique included measurements of the inter-operator and intra-operator variability in the outcome of scaphoid fixation using the proposed procedure, and also included comparison of the performance of this procedure with the conventional percutaneous fixation technique using fluoroscopy. The results showed that the tight accuracy requirements of percutaneous scaphoid fixation were met and that the consistency was superior to the conventional technique.
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Medical image analysis · Feb 2008
Myocardial deformation recovery from cine MRI using a nearly incompressible biventricular model.
This paper presents a method for biventricular myocardial deformation recovery from cine MRI. The method is based on a deformable model that is nearly incompressible, a desirable property since the myocardium has been shown to be nearly incompressible. The model uses a matrix-valued radial basis function to represent divergence-free displacement fields, which is a first order approximation of incompressibility. ⋯ The recovered strains of the normal subjects were clearly stronger than the recovered strains of the patients and they were similar to those reported by other researchers. The recovered deformation of all six subjects was validated against manual segmentation of the biventricular wall and against corresponding tagged MRI scans. The agreement was similar to that of the first study.