Abstract: A solid state LIDAR transmitter with matrix-addressable laser drive circuit includes a first electrical bus that provides a first voltage potential to columns of the matrix-addressable laser drive circuit and a second electrical bus that provide a second voltage potential to rows of the matrix-addressable laser drive circuit. A plurality of column switches connects the plurality of columns to the first electrical bus. A plurality of row switches connects the plurality of rows to the second electrical bus. The transmitter includes a plurality of series connected diodes comprising a laser diode in series with another diode, where a respective one of the plurality of series connected diodes is electrically connected between a respective column and row of the matrix-addressable laser drive circuit to form the LIDAR transmitter. At least some of the second diodes increasing an overall reverse breakdown voltage of the series connected diodes.

Abstract: A volumetric segmentation method is disclosed for brain region analysis, in particular but not limited to, regions of the basal ganglia such as the subthalamic nucleus (STN). This serves for visualization and localization within the sub-cortical region of the basal ganglia, as an example of prediction of a region of interest for deep brain stimulation procedures. A statistical shape model is applied for variation modes of the STN, or the corresponding regions of interest, and its predictors on high-quality training sets obtained from high-field, e.g., 7T, MR imaging. The partial least squares regression (PLSR) method is applied to induce the spatial relationship between the region to be predicted, e.g., STN, and its predictors. The prediction accuracy for validating the invention is evaluated by measuring the shape similarity and the errors in position, size, and orientation between manually segmented STN and its predicted one.

Abstract: A volumetric segmentation method is disclosed for brain region analysis, in particular but not limited to, regions of the basal ganglia such as the subthalamic nucleus (STN). This serves for visualization and localization within the sub-cortical region of the basal ganglia, as an example of prediction of a region of interest for deep brain stimulation procedures. A statistical shape model is applied for variation modes of the STN, or the corresponding regions of interest, and its predictors on high-quality training sets obtained from high-field, e.g., 7 T, MR imaging. The partial least squares regression (PLSR) method is applied to induce the spatial relationship between the region to be predicted, e.g., STN, and its predictors. The prediction accuracy for validating the invention is evaluated by measuring the shape similarity and the errors in position, size, and orientation between manually segmented STN and its predicted one.

Abstract: A system and method are provided for creating magnetic resonance (MR) images with reduced motion artifacts from the MR data from which the images are produced. The method includes selecting a candidate image from a plurality of candidate images reconstructed from the MR data. The method also includes registering the candidate image to a reference image, comparing the candidate image to a consistency map, and, based on comparing the candidate image using the consistency map, selecting a blending algorithm. The method also includes generating a blended image using the blending algorithm and the candidate image and repeating these steps for each candidate image. The method also includes performing a Fourier aggregation to generate a combined image and displaying the combined image with reduced motion artifacts compared to the plurality of candidate images.

Abstract: A volumetric segmentation method is disclosed for brain region analysis, in particular but not limited to, regions of the basal ganglia such as the subthalamic nucleus (STN). This serves for visualization and localization within the sub-cortical region of the basal ganglia, as an example of prediction of a region of interest for deep brain stimulation procedures. A statistical shape model is applied for variation modes of the STN, or the corresponding regions of interest, and its predictors on high-quality training sets obtained from high-field, e.g., 7T, MR imaging. The partial least squares regression (PLSR) method is applied to induce the spatial relationship between the region to be predicted, e.g., STN, and its predictors. The prediction accuracy for validating the invention is evaluated by measuring the shape similarity and the errors in position, size, and orientation between manually segmented STN and its predicted one.

Abstract: Systems and method for measuring and mitigating radio frequency (“RF”) induced currents on electrical leads, electrodes, and other electrically conductive objects present in the bore of a magnetic resonance imaging (“MRI”) scanner when the MRI scanner is operated to image an object or subject are described. The methods described in the present disclosure can be implemented as a pre-scan procedure to obtain images from which the current induced on the electrical lead can be estimated. This information can then be used to adjust the RF excitation used in a subsequent pulse sequence to mitigate induced currents and reduce heating in the lead. As such, the methods described in the present disclosure provide for improved patient safety.

Abstract: A volumetric segmentation method is disclosed for brain region analysis, in particular but not limited to, regions of the basal ganglia such as the subthalamic nucleus (STN). This serves for visualization and localization within the sub-cortical region of the basal ganglia, as an example of prediction of a region of interest for deep brain stimulation procedures. A statistical shape model is applied for variation modes of the STN, or the corresponding regions of interest, and its predictors on high-quality training sets obtained from high-field, e.g., 7T, MR imaging. The partial least squares regression (PLSR) method is applied to induce the spatial relationship between the region to be predicted, e.g., STN, and its predictors. The prediction accuracy for validating the invention is evaluated by measuring the shape similarity and the errors in position, size, and orientation between manually segmented STN and its predicted one.

Abstract: A system comprising a processor configured to: provide a master Three-Dimensional (3D) scene: insert at least one source video feed into at least one position within the master 3D scene, allowing a configuration in which at least a first part of the master 3D scene is in front of the source video feed and at least a second part of the master 3D scene is behind the source video feed; and generate a combined video of the master 3D scene with the at least one source video feed inserted therein.

Abstract: A system comprising a processor configured to: provide a master Three-Dimensional (3D) scene; insert at least one source video feed into at least one position within the master 3D scene, allowing a configuration in which at least a first part of the master 3D scene is in front of the source video feed and at least a second part of the master 3D scene is behind the source video feed; and generate a combined video of the master 3D scene with the at least one source video feed inserted therein.

Abstract: Systems and method for measuring and mitigating radio frequency (“RF”) induced currents on electrical leads, electrodes, and other electrically conductive objects present in the bore of a magnetic resonance imaging (“MRI”) scanner when the MRI scanner is operated to image an object or subject are described. The methods described in the present disclosure can be implemented as a pre-scan procedure to obtain images from which the current induced on the electrical lead can be estimated. This information can then be used to adjust the RF excitation used in a subsequent pulse sequence to mitigate induced currents and reduce heating in the lead. As such, the methods described in the present disclosure provide for improved patient safety.

Abstract: A system comprising a processor configured to: provide a master Three-Dimensional (3D) scene; insert at least one source video feed into at least one position within the master 3D scene, allowing a configuration in which at least a first part of the master 3D scene is in front of the source video feed and at least a second part of the master 3D scene is behind the source video feed; and generate a combined video of the master 3D scene with the at least one source video feed inserted therein.

Abstract: A volumetric segmentation method is disclosed for brain region analysis, in particular but not limited to, regions of the basal ganglia such as the subthalamic nucleus (STN). This serves for visualization and localization within the sub-cortical region of the basal ganglia, as an example of prediction of a region of interest for deep brain stimulation procedures. A statistical shape model is applied for variation modes of the STN, or the corresponding regions of interest, and its predictors on high-quality training sets obtained from high-field, e.g., 7T, MR imaging. The partial least squares regression (PLSR) method is applied to induce the spatial relationship between the region to be predicted, e.g., STN, and its predictors. The prediction accuracy for validating the invention is evaluated by measuring the shape similarity and the errors in position, size, and orientation between manually segmented STN and its predicted one.

Abstract: A volumetric segmentation method is disclosed for brain region analysis, in particular but not limited to, regions of the basal ganglia such as the subthalamic nucleus (STN). This serves for visualization and localization within the sub-cortical region of the basal ganglia, as an example of prediction of a region of interest for deep brain stimulation procedures. A statistical shape model is applied for variation modes of the STN, or the corresponding regions of interest, and its predictors on high-quality training sets obtained from high-field, e.g., 7T, MR imaging. The partial least squares regression (PLSR) method is applied to induce the spatial relationship between the region to be predicted, e.g., STN, and its predictors. The prediction accuracy for validating the invention is evaluated by measuring the shape similarity and the errors in position, size, and orientation between manually segmented STN and its predicted one.

Abstract: A volumetric segmentation method is disclosed for brain region analysis, in particular but not limited to, regions of the basal ganglia such as the subthalamic nucleus (STN). This serves for visualization and localization within the sub-cortical region of the basal ganglia, as an example of prediction of a region of interest for deep brain stimulation procedures. A statistical shape model is applied for variation modes of the STN, or the corresponding regions of interest, and its predictors on high-quality training sets obtained from high-field, e.g., 7 T, MR imaging. The partial least squares regression (PLSR) method is applied to induce the spatial relationship between the region to be predicted, e.g., STN, and its predictors. The prediction accuracy for validating the invention is evaluated by measuring the shape similarity and the errors in position, size, and orientation between manually segmented STN and its predicted one.

Abstract: A volumetric segmentation method is disclosed for brain region analysis, in particular but not limited to, regions of the basal ganglia such as the subthalamic nucleus (STN). This serves for visualization and localization within the sub-cortical region of the basal ganglia, as an example of prediction of a region of interest for deep brain stimulation procedures. A statistical shape model is applied for variation modes of the STN, or the corresponding regions of interest, and its predictors on high-quality training sets obtained from high-field, e.g., 7 T, MR imaging. The partial least squares regression (PLSR) method is applied to induce the spatial relationship between the region to be predicted, e.g., STN, and its predictors. The prediction accuracy for validating the invention is evaluated by measuring the shape similarity and the errors in position, size, and orientation between manually segmented STN and its predicted one.

Abstract: A volumetric segmentation method is disclosed for brain region analysis, in particular but not limited to, regions of the basal ganglia such as the subthalamic nucleus (STN). This serves for visualization and localization within the sub-cortical region of the basal ganglia, as an example of prediction of a region of interest for deep brain stimulation procedures. A statistical shape model is applied for variation modes of the STN, or the corresponding regions of interest, and its predictors on high-quality training sets obtained from high-field, e.g., 7T, MR imaging. The partial least squares regression (PLSR) method is applied to induce the spatial relationship between the region to be predicted, e.g., STN, and its predictors. The prediction accuracy for validating the invention is evaluated by measuring the shape similarity and the errors in position, size, and orientation between manually segmented STN and its predicted one.

Abstract: Theft prevention device for enabling to lock the handlebar grip and the brake-lever of a two-wheeled vehicle, where the brake-lever is movably connected to the handlebar, to prevent stealing of the vehicle. The device may comprise a housing comprising at least two openings; a handlebar cuff that enables slidably attaching to the housing through the openings and cuffing of the handlebar grip therein; a brake-lever cuff that enables slidably attaching to the housing through the openings and, cuffing of the brake-lever therein; and a lock assembly that is operatively associated with the cuffs. The lock assembly enables locking the cuffs in a position where the cuffs cuff the handlebar grip and the brake-lever. To install the theft prevention device the cuffs should be approximate to one another, and then the user may lock the cuffs in the approximated cuffing position, using the lock assembly.

Abstract: Theft prevention device for enabling to lock the handlebar grip and the brake-lever of a two-wheeled vehicle, where the brake-lever is movably connected to the handlebar, to prevent stealing of the vehicle. The device may comprise a housing comprising at least two openings; a handlebar cuff that enables slidably attaching to the housing through the openings and cuffing of the handlebar grip therein; a brake-lever cuff that enables slidably attaching to the housing through the openings and, cuffing of the brake-lever therein; and a lock assembly that is operatively associated with the cuffs. The lock assembly enables locking the cuffs in a position where the cuffs cuff the handlebar grip and the brake-lever. To install the theft prevention device the cuffs should be approximate to one another, and then the user may lock the cuffs in the approximated cuffing position, using the lock assembly.