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The segmentation of digitized data to divide a free form surface into patches is one of the key steps required to perform a reverse engineering process of an object. To this end, discrete curvature approximations are introduced as the basis of a segmentation process that lead to a decomposition of digitized data into areas that will help the construction of parametric surface patches. The proposed approach relies on the use of a polyhedral representation of the object built from the digitized data input. Then, it is shown how noise reduction, edge swapping techniques and adapted remeshing schemes can participate to different preparation phases to provide a geometry that highlights useful characteristics for the segmentation process. The segmentation process is performed with various approximations of discrete curvatures evaluated on the polyhedron produced during the preparation phases. The segmentation process proposed involves two phases: the identification of characteristic polygonal lines and the identification of polyhedral areas useful for a patch construction process. Discrete curvature criteria are adapted to each phase and the concept of invariant evaluation of curvatures is introduced to generate criteria that are constant over equivalent meshes. A description of the segmentation procedure is provided together with examples of results for free form object surfaces. [ABSTRACT FROM AUTHOR]

Multi-qubit systems are crucial for the advancement and application of quantum science. Such systems require maintaining long coherence times while increasing the number of qubits available for coherent manipulation. For solid-state spin systems, qubit coherence is closely related to fundamental questions of many-body spin dynamics. Here we apply a coherent spectroscopic technique to characterize the dynamics of the composite solid-state spin environment of nitrogen-vacancy colour centres in room temperature diamond. We identify a possible new mechanism in diamond for suppression of electronic spin-bath dynamics in the presence of a nuclear spin bath of sufficient concentration. This suppression enhances the efficacy of dynamical decoupling techniques, resulting in increased coherence times for multi-spin-qubit systems, thus paving the way for applications in quantum information, sensing and metrology., Physics

We realize anti-reflection (AR) coatings for optical excitation and fluorescence measurements of nitrogen-vacancy (NV) color centers in bulk diamond by depositing quarter-wavelength thick silica layers on the diamondsurface. These AR coatings improve NV-diamond optical measurements by reducing optical reflection at the diamond-air interface from ≈17% to ≈2%, which allows more effective NV optical excitation and more efficient detection of NV fluorescence. We also show that diamondAR coatings eliminate standing-wave interference patterns of excitation laser intensity within bulk diamond, and thereby greatly reduce spatial variations in NV fluorescence, which can degrade spatially resolved magnetic field sensing using NV centers., Engineering and Applied Sciences, Physics

We use multipulse dynamical decoupling to increase the coherence lifetime (T2) of large numbers of nitrogen-vacancy (NV) electronic spins in room temperature diamond, thus enabling scalable applications of multispin quantum information processing and metrology. We realize an order-of-magnitude extension of the NV multispin T2 in three diamond samples with widely differing spin impurity environments. In particular, for samples with nitrogen impurity concentration ≲1 ppm, we extend T2 to >2 ms, comparable to the longest coherence time reported for single NV centers, and demonstrate a tenfold enhancement in NV multispin sensing of ac magnetic fields., Physics

A common limitation of experiments using color centers in diamond is the poor photon collection efficiency of microscope objectives due to refraction at the diamond interface. We present a simple and effective technique to detect a large fraction of photons emitted by color centers within a planar diamond sample by detecting light that is guided to the edges of the diamond via total internal reflection. We describe a prototype device using this “side-collection” technique, which provides a photon collection efficiency ≈47% and a photon detection efficiency ≈39%. We apply the enhanced signal-to-noise ratio gained from side collection to ac magnetometry using ensembles of nitrogen-vacancy (NV) color centers, and demonstrate an ac magnetic field sensitivity ≈100pT/Hz‾‾‾√, limited by added noise in the prototype side-collection device. Technical optimization should allow significant further improvements in photon collection and detection efficiency as well as subpicotesla NV-diamond magnetic field sensitivity using the side-collection technique., Physics

We demonstrate preferential orientation of nitrogen-vacancy (NV) color centers along two of four possible crystallographic axes in diamonds grown by chemical vapor deposition on the {100} face. We identify the relevant growth regime and present a possible explanation of this effect. We show that preferential orientation provides increased optical readout contrast for NV multispin measurements, including enhanced ac magnetic-field sensitivity, thus providing an important step towards high-fidelity multispin-qubit quantum information processing, sensing, and metrology., Physics

Purpose: To evaluate the diagnostic performance of three-dimensional ( 3D three-dimensional ) quantitative enhancement-based and diffusion-weighted volumetric magnetic resonance (MR) imaging assessment of hepatocellular carcinoma ( HCC hepatocellular carcinoma ) lesions in determining the extent of pathologic tumor necrosis after transarterial chemoembolization ( TACE transarterial chemoembolization )., Materials and Methods: This institutional review board-approved retrospective study included 17 patients with HCC hepatocellular carcinoma who underwent TACE transarterial chemoembolization before surgery. Semiautomatic 3D three-dimensional volumetric segmentation of target lesions was performed at the last MR examination before orthotopic liver transplantation or surgical resection. The amount of necrotic tumor tissue on contrast material-enhanced arterial phase MR images and the amount of diffusion-restricted tumor tissue on apparent diffusion coefficient ( ADC apparent diffusion coefficient ) maps were expressed as a percentage of the total tumor volume. Visual assessment of the extent of tumor necrosis and tumor response according to European Association for the Study of the Liver ( EASL European Association for the Study of the Liver ) criteria was performed. Pathologic tumor necrosis was quantified by using slide-by-slide segmentation. Correlation analysis was performed to evaluate the predictive values of the radiologic techniques., Results: At histopathologic examination, the mean percentage of tumor necrosis was 70% (range, 10%-100%). Both 3D three-dimensional quantitative techniques demonstrated a strong correlation with tumor necrosis at pathologic examination (R(2) = 0.9657 and R(2) = 0.9662 for quantitative EASL European Association for the Study of the Liver and quantitative ADC apparent diffusion coefficient , respectively) and a strong intermethod agreement (R(2) = 0.9585). Both methods showed a significantly lower discrepancy with pathologically measured necrosis (residual standard error [ RSE residual standard error ] = 6.38 and 6.33 for quantitative EASL European Association for the Study of the Liver and quantitative ADC apparent diffusion coefficient , respectively), when compared with non- 3D three-dimensional techniques ( RSE residual standard error = 12.18 for visual assessment)., Conclusion: This radiologic-pathologic correlation study demonstrates the diagnostic accuracy of 3D three-dimensional quantitative MR imaging techniques in identifying pathologically measured tumor necrosis in HCC hepatocellular carcinoma lesions treated with TACE transarterial chemoembolization ., (© RSNA, 2014 Online supplemental material is available for this article.)

We propose a method for fast, accurate and robust localization of several organs in medical images. We generalize global-to-local cascades of regression forests [1] to multiple organs. A first regressor encodes global relationships between organs. Subsequent regressors refine the localization of each organ locally and independently for improved accuracy. We introduce confidence maps, which incorporate information about both the regression vote distribution and the organ shape through probabilistic atlases. They are used within the cascade itself, to better select the test voxels for the second set of regressors, and to provide richer information than the classical bounding boxes thanks to the shape prior. We demonstrate the robustness and accuracy of our approach through a quantitative evaluation on a large database of 130 CT volumes.

Kidney segmentation in 3D CT images allows extracting useful information for nephrologists. For practical use in clinical routine, such an algorithm should be fast, automatic and robust to contrast-agent enhancement and fields of view. By combining and refining state-of-the-art techniques (random forests and template deformation), we demonstrate the possibility of building an algorithm that meets these requirements. Kidneys are localized with random forests following a coarse-to-fine strategy. Their initial positions detected with global contextual information are refined with a cascade of local regression forests. A classification forest is then used to obtain a probabilistic segmentation of both kidneys. The final segmentation is performed with an implicit template deformation algorithm driven by these kidney probability maps. Our method has been validated on a highly heterogeneous database of 233 CT scans from 89 patients. 80% of the kidneys were accurately detected and segmented (Dice coefficient > 0.90) in a few seconds per volume.

We propose a recursive Bayesian model for the delineation of coronary arteries from 3D CT angiograms (cardiac CTA) and discuss the use of discrete minimal path techniques as an efficient optimization scheme for the propagation of model realizations on a discrete graph. Design issues such as the definition of a suitable accumulative metric are analyzed in the context of our probabilistic formulation. Our approach jointly optimizes the vascular centerline and associated radius on a 4D space+scale graph. It employs a simple heuristic scheme to dynamically limit scale-space exploration for increased computational performance. It incorporates prior knowledge on radius variations and derives the local data likelihood from a multiscale, oriented gradient flux-based feature. From minimal cost path techniques, it inherits practical properties such as computational efficiency and workflow versatility. We quantitatively evaluated a two-point interactive implementation on a large and varied cardiac CTA database. Additionally, results from the Rotterdam Coronary Artery Algorithm Evaluation Framework are provided for comparison with existing techniques. The scores obtained are excellent (97.5% average overlap with ground truth delineated by experts) and demonstrate the high potential of the method in terms of robustness to anomalies and poor image quality.