IEEE transactions on medical imaging
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IEEE Trans Med Imaging · Feb 2007
Outlier detection and handling for robust 3-D active shape models search.
This paper presents a new outlier handling method for volumetric segmentation with three-dimensional (3-D) active shape models. The method is based on a shape metric that is invariant to scaling, rotation and translation by using the ratio of interlandmark distances as a local shape dissimilarity measure. Tolerance intervals for the descriptors are calculated from the training samples and used as a statistical tolerance model to infer the validity of the feature points. ⋯ A geometrically weighted fitness measure is introduced for feature point detection, which limits the presence of outliers and improves the convergence of the proposed segmentation framework. The algorithm is immune to the extremity of the outliers and can handle a highly significant presence of erroneous feature points. The practical value of the technique is validated with 3-D magnetic resonance (MR) segmentation tasks of the carotid artery and myocardial borders of the left ventricle.
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IEEE Trans Med Imaging · Jan 2007
Volumetric texture segmentation by discriminant feature selection and multiresolution classification.
In this paper, a multiresolution volumetric texture segmentation (M-VTS) algorithm is presented. The method extracts textural measurements from the Fourier domain of the data via subband filtering using an orientation pyramid (Wilson and Spann, 1988). A novel Bhattacharyya space, based on the Bhattacharyya distance, is proposed for selecting the most discriminant measurements and producing a compact feature space. ⋯ The classified voxel labels are then projected to lower levels of the tree where a boundary refinement procedure is performed with a three-dimensional (3-D) equivalent of butterfly filters. The algorithm was tested with 3-D artificial data and three magnetic resonance imaging sets of human knees with encouraging results. The regions segmented from the knees correspond to anatomical structures that can be used as a starting point for other measurements such as cartilage extraction.
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IEEE Trans Med Imaging · Jan 2007
Segmenting articular cartilage automatically using a voxel classification approach.
We present a fully automatic method for articular cartilage segmentation from magnetic resonance imaging (MRI) which we use as the foundation of a quantitative cartilage assessment. We evaluate our method by comparisons to manual segmentations by a radiologist and by examining the interscan reproducibility of the volume and area estimates. ⋯ While high-field scanners offer high-quality imaging from which the articular cartilage have been evaluated extensively using manual and automated image analysis techniques, low-field scanners on the other hand produce lower quality images but to a fraction of the cost of their high-field counterpart. For low-field MRI, there is no well-established accuracy validation for quantitative cartilage estimates, but we show that differences between healthy and osteoarthritic populations are statistically significant using our cartilage volume and surface area estimates, which suggests that low-field MRI analysis can become a useful, affordable tool in clinical studies.
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IEEE Trans Med Imaging · Jan 2007
Tracking myocardial motion from cine DENSE images using spatiotemporal phase unwrapping and temporal fitting.
Displacement encoding with stimulated echoes (DENSE) encodes myocardial tissue displacement into the phase of the MR image. Cine DENSE allows for rapid quantification of myocardial displacement at multiple cardiac phases through the majority of the cardiac cycle. For practical sensitivities to motion, relatively high displacement encoding frequencies are used and phase wrapping typically occurs. ⋯ The accuracy of the tracking algorithm for typical cardiac displacements on a rotating phantom is 0.24 +/- 0.15 mm. The optimal displacement encoding frequency is in the region of 0.1 cycles/mm, and, for 2 scans of 17-s duration, the strain noise after temporal fitting was estimated to be 2.5 +/- 3.0% at end-diastole, 3.1 +/- 3.1% at end-systole, and 5.3 +/- 5.0% in mid-diastole. The improvement in intra-myocardial strain measurements due to temporal fitting is apparent in strain histograms, and also in identifying regions of dysfunctional myocardium in studies of patients with infarcts.
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IEEE Trans Med Imaging · Jan 2007
The effects of flow dispersion and cardiac pulsation in arterial spin labeling.
The blood in the carotid arteries exhibits time-varying flow velocity as a function of cardiac phases. Despite this flow velocity variation, most current methods set forth for the analysis of arterial spin labeling (ASL) data have assumed that the tagged blood is delivered from the tagging region to the imaging region via simple plug flow, i.e., a single transit delay (deltat). In this study, we used a pulse oximeter to synchronize image acquisition at systole and diastole separately. ⋯ Intervoxel dispersion (-350 ms) dominated over intravoxel dispersion (< 200 ms). The disparity of ASL signals found between systolic and diastolic tags indicated that ASL imaging was sensitive to cardiac pulsations. We conclude that both flow dispersion and fluctuations in the ASL signal due to cardiac pulsations are significant.