Abstract: A back-driving handle assembly for protecting a gaming machine from damage when the back-driving handle assembly is loaded in reverse. The back-driving handle assembly includes tuned counter-opposing springs and a ratchet plate with a specially designed tooth angle. The back-driving handle assembly allows normally locking ratchet and pawl to slip past some teeth on an overload condition, thus preserving functionalities of the back-driving handle assembly.

Abstract: Methods, Apparatuses, and Systems of operating a laser atherectomy system to perform an endoscopic atherectomy procedure within a vessel at a therapeutic region of an anatomical condition by use of an atherectomy laser device coupled to an ultrasound imaging probe. The atherectomy laser device operates to generate photoacoustic signals from a light source of the atherectomy laser device to for guidance within the vessel and to characterize tissue about the therapeutic region by delivery of pulsed wavelengths within the vessel, and to perform operations of tissue ablation directed to the anatomical condition. This enables guidance of the atherectomy laser device by feedback from the viewing of photoacoustic images based on photoacoustic signals generated the atherectomy laser device and created in response to changes in acoustic intensity due to changes of optical wavelength monitored by the ultrasound imaging probe.

Abstract: Systems and methods for laser catheter treatment in a vessel lumen. The method includes inserting the laser catheter within the vessel lumen to a location of a treatment area; presenting an image of the treatment area within the vessel lumen based on using an ultrasound (US) imaging system; and, detecting, in real-time, a bubble cloud that is a function of the laser catheter operation (at a prescribed speed and controlling a fluence and a pulse rate) in the treatment area. The method determines a vessel diameter, a real-time location and measurements of the bubble cloud, and estimates a dwell position and dwell time. A dynamic displayed image that is indicative of a progression of the laser catheter treatment is presented, and commands may be generated to modify the laser catheter parameters responsive to the estimated dwell position, the estimated dwell time, and a recommended treatment protocol.

Abstract: Various embodiments of the present disclosure encompass an endoluminal therapy system employing an endoluminal therapy device (21) and an endoluminal therapy monitoring controller (10). In support an endoluminal procedure, the endoluminal therapy device (21) is controlled to treat a site to be treated within a lumen. The controller (10) is operated to synchronize an activated dwell timing of the endoluminal therapy device (21) within the lumen to a tracked positioning of the endoluminal therapy device (21) contiguous with the site to be treated within the lumen. The controller (10) is further operated to monitor the site to be treated within the lumen induced by the endoluminal therapy device (21) during the synchronization by the controller (10) of the activated dwell timing of the endoluminal therapy device (21) within the lumen to the tracked positioning of the endoluminal therapy device (21) contiguous with the site to be treated within the lumen.

Abstract: Disclosed is an ultrasound roadmap image generation system. The system includes a processor configured for communication with an ultrasound imaging device that is movable relative to a patient. The processor receives a first bi-plane or 3D image representative of a first volume within the patient and a second bi-plane or 3D image representative of a second volume within the patient. The processor then registers the first bi-plane or 3D image and the second bi-plane or 3D image to determine the motion between the first bi-plane or 3D image and the second bi-plane or 3D image. The processor then generates a 2D roadmap image of a region of interest by combining the first bi-plane or 3D image and the second bi-plane or 3D image, based on the determined motion; and outputs a screen display comprising the 2D roadmap image.

Abstract: A controller (210) for tracking an interventional medical device (252) in three dimensions includes a memory (212) that stores instructions, and a processor (211) that executes the instructions. When executed by the processor (211), the instructions cause the controller (210) to execute a process. The process includes determining (S320/S420), based on an elevation plane in an ultrasound X-plane mode, a first two-dimensional location of the interventional medical device (252) in the elevation plane. The process also includes determining (S320/S422), based on an azimuthal plane in the ultrasound X-plane mode, a second two-dimensional location of the interventional medical device (252) in the azimuthal plane. The process moreover includes determining (S330/S430), based on the first two-dimensional location and the second two-dimensional location, a three-dimensional location of the interventional medical device (252).

Abstract: The systems and methods monitor additive manufacturing using a statistical time-frequency domain algorithm. Some embodiments utilize the periodicity of the scan-line (or “raster”) pattern of the laser in an additive manufacturing machine to define a nominal performance baseline for the machine in the time-frequency domain. The nominal basis is established by processing a series of images of the melt pool of the machine during scanning by the laser and converting this data to a spectrogram. The operation of the machine can then be monitored against this nominal basis in substantially real-time in some embodiments by comparing the spectrogram generated from operational data to the nominal basis.

Abstract: A device and method for directing a cannula toward a target location under a patient's skin. The device is handheld and the device operations may be automated. The device includes an imaging probe for imaging the target location, a positioning unit for manipulating a cannula towards the target location, and a processor. The processor receives imaging data from the imaging probe, cannula pose data from at least one cannula position sensor, and device pose data from at least one device position sensor. The target location is identified from the imaging data, and a trajectory for manipulating the cannula towards the target location is determined based on the imaging data, the cannula pose data, and the device pose data. The processor may determine that the trajectory becomes misaligned with the target position, and may update to a corrected trajectory based on the imaging data, cannula pose data, and device pose data.

Abstract: A back-driving handle assembly for protecting a gaming machine from damage when the back-driving handle assembly is loaded in reverse. The back-driving handle assembly includes tuned counter-opposing springs and a ratchet plate with a specially designed tooth angle. The back-driving handle assembly allows normally locking ratchet and pawl to slip past some teeth on an overload condition, thus preserving functionalities of the back-driving handle assembly.

Abstract: A method and system is for assisting a user in positioning an ultrasound probe relative to a subject's body. In use, the user moves the probe through a series of positions, and ultrasound image data is captured for each position, the data at each position corresponding to a particular imaging view of the anatomical region being imaged. An assessment procedure (16) is operable to process ultrasound data for different imaging views, and to determine for the data for each view a rating, representative of the suitability of the data for that view for observing one or more anatomical features or deriving one or more clinical parameters from the data. Guidance feedback is generated (18) for the user for assisting the user in positioning the probe, wherein the guidance feedback is based on a history (26) of image view quality over time over the course of the imaging procedure.

Abstract: A system for localizing a three-dimensional field of view of a beamforming ultrasound imaging probe based on a position indicator disposed within said field of view. The beamforming ultrasound imaging probe transmits and receives ultrasound signals within a three-dimensional field of view comprising a plurality of predetermined sub-volumes, each sub-volume being defined by a two dimensional array of beams. A controller causes the beamforming ultrasound imaging probe to scan the sub-volumes sequentially by transmitting and receiving ultrasound signals corresponding to each beam. A tracking system determines a position of the position indicator within the three-dimensional field of view; and determines a sub-volume in which the position indicator is located.

Abstract: A method (100) for analyzing ultrasound image data, comprising: (i) receiving (120) ultrasound image data for a patient, comprising at least one lung-related clinical feature; (ii) selecting (130) a first clinical feature; (iii) analyzing (140), using an image processing algorithm, the ultrasound image data to extract one or more image parameters of the selected clinical feature, wherein the image processing algorithm is defined to analyze the selected clinical feature; (iv) analyzing (150), using a trained machine learning algorithm, the ultrasound image data to extract one or more learned parameters of the selected clinical feature, wherein the trained machine learning algorithm is trained to analyze the selected clinical feature; (v) combining (160) the image parameters and the learned parameters to generate a final lung-related clinical feature analysis; and (vi) providing (170) the generated final lung-related clinical feature analysis.

Abstract: A method (100) for analyzing ultrasound image data, comprising: (i) receiving (120) a temporal sequence of ultrasound image data for one or more of a plurality of different zones of one or both lungs of a patient; (ii) analyzing (130), using a first trained clinical lung feature identification algorithm, the received ultrasound image data to identify a first clinical feature in a lung of the patient, wherein identifying the first clinical feature comprises analysis of multiple frames in the temporal sequence, and wherein identifying the first clinical feature comprises identification of a location of the first clinical feature within the multiple frames; (iii) analyzing (140), using a trained clinical lung feature severity algorithm, the identified first clinical feature to characterize a severity of the identified first clinical feature; and (iv) providing (180), via a user interface, the identified first clinical feature and the characterized severity of the first clinical feature.

Abstract: A device and method for directing a cannula toward a target location under a patient's skin. The device is handheld and the device operations may be automated. The device includes an imaging probe for imaging the target location, a positioning unit for manipulating a cannula towards the target location, and a processor. The processor receives imaging data from the imaging probe, cannula pose data from at least one cannula position sensor, and device pose data from at least one device position sensor. The target location is identified from the imaging data, and a trajectory for manipulating the cannula towards the target location is determined based on the imaging data, the cannula pose data, and the device pose data. The processor may determine that the trajectory becomes misaligned with the target position, and may update to a corrected trajectory based on the imaging data, cannula pose data, and device pose data.

Abstract: A system for power consumption management for an electronic gaming environment includes at least one memory device with instructions stored thereon. The at least one memory device further storing a plurality of energy profiles, each of the energy profiles defining a set of control operations for at least one electronic gaming device. The system further includes at least one processor in communication with the at least one memory device. The instructions, when executed by the at least one processor, cause the at least one processor to receive a power adjustment command, select, based on the power adjustment command, a first energy profile of the plurality of energy profiles, and control the at least one electronic gaming device to adjust power consumption based on the first energy profile.

Abstract: A method (100) for providing localization information using an ultrasound system (200), comprising: receiving (140) a plurality of ultrasound images for a first imaged region; receiving (150), via a user interface, a user input comprising location information about the first imaged region; processing (160), using a trained localization algorithm, both: (i) one or more of the received plurality of ultrasound images and (ii) the received user input to generate a localization report for the first imaged region, the localization report comprising one or more of a coordinate, a contour, and a structure identification; and providing (170), via a user interface, the localization report to a user.

Abstract: A system for localizing a three-dimensional field of view of a beamforming ultrasound imaging probe based on a position indicator disposed within said field of view. The beamforming ultrasound imaging probe transmits and receives ultrasound signals within a three-dimensional field of view comprising a plurality of predetermined sub-volumes, each sub-volume being defined by a two dimensional array of beams. A controller causes the beamforming ultrasound imaging probe to scan the sub-volumes sequentially by transmitting and receiving ultrasound signals corresponding to each beam. A tracking system determines a position of the position indicator within the three-dimensional field of view; and determines a sub-volume in which the position indicator is located.

Abstract: A controller (522) for live annotation of interventional imagery includes a memory (52220) that stores software instructions and a processor (52210) that executes the software instructions. When executed by the processor (52210), the software instructions cause the controller (522) to implement a process that includes receiving (S210) interventional imagery during an intraoperative intervention and automatically analyzing (S220) the interventional imagery for detectable features. The process executed when the processor (52210) executes the software instructions also includes detecting (S230) a detectable feature and determining (S240) at add an annotation to the interventional imagery for the detectable feature. The processor further includes identifying (S250) a location for the annotation as an identified location in the interventional imagery and adding (S260) the annotation to the interventional imagery at the identified location to correspond to the detectable feature.

Abstract: A pleural line may be determined based on initially determining a location of a rib shadow region and subsequently a rib surface. A first region of interest (ROI) may be automatically selected within an ultrasound image acquired from a lung ultrasound scan of a patient based, at least in part, on a depth of the image. The first ROI may be analyzed to determine at least one rib shadow region. The rib shadow region may be used to automatically select a second ROI. The second ROI may be analyzed to determine a location of a rib surface. The location of the rib surface may be used to automatically select a third ROI. The third ROI may be analyzed to determine the pleural line.

Abstract: A method (100) for analyzing ultrasound image data, comprising: (i) receiving (120) ultrasound image data for a patient, comprising at least one lung-related clinical feature; (ii) selecting (130) a first clinical feature; (iii) analyzing (140), using an image processing algorithm, the ultrasound image data to extract one or more image parameters of the selected clinical feature, wherein the image processing algorithm is defined to analyze the selected clinical feature; (iv) analyzing (150), using a trained machine learning algorithm, the ultrasound image data to extract one or more learned parameters of the selected clinical feature, wherein the trained machine learning algorithm is trained to analyze the selected clinical feature; (v) combining (160) the image parameters and the learned parameters to generate a final lung-related clinical feature analysis; and (vi) providing (170) the generated final lung-related clinical feature analysis.