Showing papers in "Medical Image Analysis in 2008"
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TL;DR: This study indicates that SyN, with cross-correlation, is a reliable method for normalizing and making anatomical measurements in volumetric MRI of patients and at-risk elderly individuals.
4,233 citations
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TL;DR: From the results over synthetic and real images, it can be concluded that this recently proposed filter for random noise removal can be successfully used for automatic MR denoising.
510 citations
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TL;DR: A novel and efficient approach to dense image registration, which does not require a derivative of the employed cost function is introduced, and efficient linear programming using the primal dual principles is considered to recover the lowest potential of the cost function.
469 citations
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TL;DR: This paper presents a fully automated multi-target tracking system that can efficiently cope with these challenges while simultaneously tracking and analyzing thousands of cells observed using time-lapse phase contrast microscopy.
415 citations
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TL;DR: New methods that allow one to simulate medical ultrasound from CT in real-time, reproducing the majority of ultrasonic imaging effects are developed, along with a robust similarity measure.
376 citations
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TL;DR: A registration-based technique for estimating local lung expansion from multiple respiratory-gated CT images of the thorax using the Jacobian of the registration displacement field is described, which it is shown is directly related to specific volume change.
324 citations
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TL;DR: A 44-fold increase in fitting speed and a segmentation accuracy that is on par with Gauss-Newton optimization, one of the most widely used optimization algorithms for such problems.
318 citations
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TL;DR: The constitutive model corresponding to the "average" liver response has been implemented into a finite element whole liver model and used for simulations related to liver surgery and the predictive capabilities of the quasi-linear viscoelastic model and the Rubin Bodner non-linear elastic-viscoplastic model are compared.
223 citations
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TL;DR: Despite limitations on the regions of bone accessible using US imaging, this technique has potential as a cost-effective and non-invasive method to enable surgical navigation during CAOS procedures, without the additional radiation dose associated with performing a preoperative CT scan or intraoperative fluoroscopic imaging.
159 citations
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TL;DR: A new intensity mapping technique is presented allowing to replace MI by more reliable measures for small patches and allows the use of the more robust and computationally more efficient cross-correlation coefficient for the matching at lower levels of the hierarchy.
151 citations
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TL;DR: A robotically assisted prostate brachytherapy system and test results in training phantoms and Phase-I clinical trials are presented, to determine whether the apparent benefits of the robotic assistant will lead to improvements in clinical efficacy and outcomes.
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TL;DR: A novel approach for joint clustering and point-by-point mapping of white matter fiber pathways and the proposed method has the potential to benefit from an anatomical atlas of fiber tracts by incorporating it as prior information in the EM algorithm.
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TL;DR: A new computer aided detection (CAD) system is presented for the detection of pulmonary nodules on chest radiographs and a novel candidate segmentation algorithm is proposed that uses an adaptive distance-based threshold.
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TL;DR: Results showed that the proposed technique is robust, accurate, and reproducible to perform point to point inter-subject comparison of knee cartilage thickness values.
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TL;DR: This paper presents a method for biventricular myocardial deformation recovery from cine MRI based on a deformable model that is nearly incompressible, a desirable property since the myocardium has been shown to be nearly incompressed.
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TL;DR: This paper explores the use of topological information as a prior and proposes a segmentation framework based on both topological and statistical atlases of brain anatomy, and guarantees strict topological equivalence between the segmented image and the atlas, and relies only weakly on a statistical atlas of shape.
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TL;DR: This work proposes an improved, fully automated particle filtering algorithm for the tracking of many subresolution objects in fluorescence microscopy image sequences that involves a new track management procedure and allows the use of multiple dynamics models.
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TL;DR: The results demonstrate that the template-based atlas-to-patient warping technique is the best of the three for customizing the atlas onto patient data.
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TL;DR: This paper employs a generative model for the joint registration and segmentation of images and finds that the optimal segmentation (parcellation) corresponds to a unique balance of atlas sharpness and warp regularization, yielding statistically significant improvements over the FreeSurfer parcellation algorithm.
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TL;DR: This paper proposes to infer a statistical brain model from the consistent integration of variability of sulcal lines, and its current-based diffeomorphic registration (CDR) approach is carefully compared to a pointwise line correspondences (PLC) method.
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TL;DR: 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 is presented.
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TL;DR: This article presents a method to introduce more coherence in the registration by using fewer degrees of freedom than with a dense registration, using a set of affine transformations, which are optimized together in a very efficient manner.
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TL;DR: It is shown that integration can be applied in a hierarchical fashion to quantify functional interactions between compound systems, each system being composed of several regions.
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TL;DR: A robust automatic initialization of an active shape model of the prostate, which is subsequently fitted to the boundary of the gland, based on pixel classification to estimate the prostate region in an ultrasound image, followed by automatic adjustment of the initial pose to the binary image produced by the classifier.
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TL;DR: This paper describes how two multivariate statistical techniques can be used to quantify and predict correlated behaviour in sub-cortical structures within the brain using 3D MR images.
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TL;DR: An algorithm for the automatic artery recognition in longitudinal US scans of the common carotid artery acts directly on the envelopes of received radio frequency echo signals, eventually composing the ultrasound image.
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TL;DR: A novel geometric flow for segmenting vasculature in PD images is developed, which can be applied to the easier cases of MR angiography data or Gadolinium enhanced MRI volumes and a new way to visualize the segmentations in 2D with masked projections is suggested.
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TL;DR: The proposed method, referred to as Bilinear Deformable Block Matching (BDBM), uses a bilinear model with eight parameters for controlling the local mesh deformation and outperforms the usual block matching.
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TL;DR: An image-based adaptive density-correction method for minimizing the pseudo-enhancement effect in fecal-tagging CT colonography data and for improving CAD performance in CTC is developed.
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TL;DR: The smoothed shape operators method (SSO) is presented, which uses a geometry processing approach to extract a triangle mesh representation of the colon surface, and estimate curvature on this surface using the shape operator.