Abstract: A system for diagnosing an esophageal disease includes at least one processor and at least one memory storing instructions. The instructions, when executed by the at least one processor, cause the system to: access, during a procedure involving an in-vivo device located within a person, data measured by the in-vivo device relating to an esophageal disease; evaluate, during the procedure while the in-vivo device is located within the person, a diagnosis for the esophageal disease for the person by applying a trained machine learning model to the data measured by the in-vivo device; and communicate, during the procedure while the in-vivo device is located within the person, the diagnosis for the esophageal disease.

Abstract: Methods, system and computer program product, the method comprising: from high level language code (HLLC), receiving a request for reading a data set from a tape onto an object storage connected over TCP/IP to a mainframe; from the HLLC, allocating a data set on a tape comprising information to be imported, the allocation being in a format of the stored data set record and associated with a JFCB, the tape is mounted in SL mode; updating the JFCB to BLP mode; reading from the tape VOL1 data, and for each stored file initiating by the HLLC: reading HDR1/2, content block-by-block; EOF1/2 of the file; organizing the VOL1, HDR1, HDR2, content, EOF1 and EOF2 in the object storage; and closing the tape, wherein said reading is performed without setting a JES of the mainframe to BLP mode, and said reading is performed without unmounting the tape after each file.

Abstract: Systems, methods, and non-transitory computer readable media including instructions for presenting location-based content are described. Presenting location-based content includes obtaining an indication of a current physical location of an extended reality appliance; providing the indication to a first server that maps physical locations to a plurality of content addresses; receiving from the first server, at least one specific content address associated with the current physical location; using the at least one specific content address to access a second server; receiving content, associated with the current physical location, from the second server; and presenting the content via the extended reality appliance, while the extended reality appliance is in the current physical location.

Abstract: A system and a method for content localization in moving vehicles may include receiving from within a moving vehicle first acceleration data captured using a first sensor included in an extended reality appliance mountable on a head of a wearer. The first acceleration data includes a first component associated with movement of the head of the wearer with respect to the vehicle and a second component associated with movement of the vehicle. The system also includes receiving from within the moving vehicle second acceleration data captured using a second sensor included in a personal input device. The personal input device may be a non-vehicle component configured to be paired with the extended reality appliance. The system may segregate the second component from the first component using the first acceleration data and the second acceleration data to thereby isolate the head acceleration with respect to the vehicle from the vehicle acceleration.

Abstract: A computer-implemented method for estimating a size of a suspected polyp in an image includes accessing an image of in at least a portion of a gastrointestinal tract (GIT) captured by a capsule endoscopy device, wherein the image includes a suspected polyp; receiving an indication to an approximated periphery of the suspected polyp in the image; determining, without human intervention, a 3D measurement of the polyp based on peripheral points in the approximated periphery indication; and estimating a size of the suspected polyp based on the determined 3D measurement.

Abstract: Systems, methods, and non-transitory computer readable media including instructions for selectively operating a wearable extended reality appliance are disclosed. Selectively operating the wearable extended reality appliance includes establishing a link between a wearable extended reality appliance and a keyboard device; receiving sensor data from at least one sensor associated with the wearable extended reality appliance, the sensor data being reflective of a relative orientation of the wearable extended reality appliance with respect to the keyboard device; based on the relative orientation, selecting from a plurality of operation modes a specific operation mode for the wearable extended reality appliance; identifying a user command based on at least one signal detected by the wearable extended reality appliance; and executing an action responding to the identified user command in a manner consistent with the selected operation mode.

Abstract: A surgical system for detecting perfusion includes at least one surgical camera and a computing device. The at least one surgical camera is configured to obtain image data of tissue at a surgical site including first image data and second image data that is temporally-spaced relative to the first image data. The computing device is configured to receive the image data from the at least one surgical camera and includes a non-transitory computer-readable storage medium storing instructions configured to cause the computing device to detect differences between the first and second image data, determine a level of perfusion in the tissue based on the detected differences between the first and second image data, and provide an output indicative of the determined level of perfusion in the tissue.

Abstract: A computer-implemented method for estimating adequacy of a capsule endoscopy (CE) procedure includes: accessing a plurality of images of at least a portion of a gastrointestinal tract (GIT) captured by a CE imaging device during a CE procedure; accessing a plurality of characteristic measures associated with the plurality of images; determining an adequacy measure for the CE procedure based on the plurality of characteristic measures, where the adequacy measure provides a measure of whether an imaging coverage provided by the plurality of images was adequate to capture an event of interest in the at least the portion of the GIT, whether or not such an event of interest actually exists in the at least the portion of the GIT; and displaying an adequacy indication for the CE procedure based on the adequacy measure.

Abstract: Systems and methods are disclosed for identifying images that contain polyps. An exemplary method for identifying images includes: accessing images of a gastrointestinal tract (GIT) captured by a capsule endoscopy device, where: each image of the images is suspected to include a polyp and is associated with a probability of containing the polyp, and the images include seed images, where each seed image is associated with one or more images of the images. The image(s) associated with each seed image is identified as suspected to include the same polyp as the associated seed image. The method includes applying a polyp detection system on the seed images to identify seed images which include polyps, where the polyp detection system is applied to each seed image of based on the image(s) associated with the seed image and the probabilities associated with the seed image and with the associated image(s).

Abstract: Systems, methods, and non-transitory computer readable media including instructions for selectively operating a wearable extended reality appliance are disclosed. Selectively operating the wearable extended reality appliance includes establishing a link between a wearable extended reality appliance and a keyboard device; receiving sensor data from at least one sensor associated with the wearable extended reality appliance, the sensor data being reflective of a relative orientation of the wearable extended reality appliance with respect to the keyboard device; based on the relative orientation, selecting from a plurality of operation modes a specific operation mode for the wearable extended reality appliance; identifying a user command based on at least one signal detected by the wearable extended reality appliance; and executing an action responding to the identified user command in a manner consistent with the selected operation mode.

Abstract: A method executed by a system for selecting images from a plurality of image groups originating from a plurality of imagers of an in-vivo device includes calculating, or otherwise associating, a general score (GS) for images of each image group, to indicate the probability that each image includes at least one pathology, dividing each image group into image subgroups, identifying a set Set(i) of maximum general scores (MGSs), a MGS for each image subgroup of each image group; and selecting images for processing by identifying a MGS|max in each set S(i) of MGSs; identifying the greatest MGS|max and selecting the image related to the greatest MGS|max. The method further includes modifying the set Set(i) of MGSs related to the selected image, and repeating the steps described above until a predetermined criterion selected from a group consisting of a number N of images and a score threshold is met.

Abstract: Methods for capturing and transmitting images by an in-vivo device comprise operating a pixel array in a superpixel readout mode to capture probe image, for example, according to a time interval. Concurrently to capturing of each probe image, the probe image is evaluated alone or in conjunction with other probe image(s), and if it is determined that no event of interest is detected by the last probe image, or by the last few probe images, the pixel array is operated in the superpixel readout mode and a subsequent probe image is captured. However, if it is determined that the last probe image, or the last few probe images, detected an event of interest, the pixel array is operated in a single pixel readout mode and a single normal image, or a series of normal image, is captured and transmitted, for example, to an external receiver.

Abstract: Systems, devices, methods for capsule endoscopy procedures are disclosed. A system for a capsule endoscopy procedure includes a capsule device configured to capture in-vivo images over time of at least a portion of a gastrointestinal tract (GIT) of a person, a wearable device configured to be secured to the person where the wearable device is configured to receive at least some of the in-vivo images from the capsule device and to communicate at least some of the received images to a communication device at a same location as the wearable device, and a storage medium storing machine-executable instructions configured to execute on a computing system remote from the location of the wearable device. The instructions, when executed, cause the computing system to receive communicated images from the communication device, perform processing of the communicated images received from the communication device, and communicate with at least one healthcare provider device.

Abstract: Systems and methods may display and/or provide analysis of a number of selected images of a patients gastrointestinal tract collected in-vivo by a swallowable capsule. Images may be displayed for review (e.g., as a study) and/or for further analysis by a user. A subset of images representing the stream of images and automatically selected according to a first selection method may be displayed. On user input, additional images corresponding to a currently displayed image may be displayed, where the additional images are automatically selected according to a second selection method. The second selection method may be based on a relation between images of the stream of in-vivo images and the currently displayed image.

Abstract: A method executed by a system for selecting images from a plurality of image groups originating from a plurality of QC imagers of an in-vivo device includes calculating, or otherwise associating, a general score (GS) for images of each image group, to indicate the probability that each image includes at least one pathology, dividing each image group into image subgroups, identifying a set Set(i) of maximum general scores (MGSs), a MGS for each image subgroup of each image group; and selecting images for processing by identifying a MGS|max in each set S(i) of MGSs; identifying the greatest MGS|max and selecting the image related to the greatest MGS1max. The method further includes modifying the set Set(i) of MGSs related to the selected image, and repeating the steps described above until a predetermined criterion selected from a group consisting of a number N of images and a score threshold is met.

Abstract: A method executed by a system for selecting images from a plurality of image groups originating from a plurality of imagers of an in-vivo device includes calculating, or otherwise associating, a general score (GS) for images of each image group, to indicate the probability that each image includes at least one pathology, dividing each image group into image subgroups, identifying a set Set(i) of maximum general scores (MGSs), a MGS for each image subgroup of each image group; and selecting images for processing by identifying a MGS|max in each set S(i) of MGSs; identifying the greatest MGS|max and selecting the image related to the greatest MGS|max. The method further includes modifying the set Set(i) of MGSs related to the selected image, and repeating the steps described above until a predetermined criterion selected from a group consisting of a number N of images and a score threshold is met.

Abstract: Systems and methods for detecting an anomaly in an image from a set of images captured in vivo by an in-vivo imaging system may include, for each pixel of the image, associating the pixel with a color histogram value from a color histogram database; determining, for each pixel, whether the color histogram value associated with the pixel exceeds a histogram value threshold; assigning a pixel status to each pixel indicating whether the pixel is anomalous or normal; identifying one or more groups of adjacent anomalous pixels, the one or more groups of adjacent anomalous pixels each having a pixel size that exceeds a pixel size threshold; generating, using at least the one or more groups of adjacent anomalous pixels, a binary mask for the image; and determining an image anomaly score for the image based at least in part on the binary mask.

Abstract: A method executed by a system for selecting images from a plurality of image groups originating from a plurality of imagers of an in-vivo device includes calculating, or otherwise associating, a general score (GS) for images of each image group, to indicate the probability that each image includes at least one pathology, dividing each image group into image subgroups, identifying a set Set(i) of maximum general scores (MGSs), a MGS for each image subgroup of each image group; and selecting images for processing by identifying a MGS|max in each set S(i) of MGSs; identifying the greatest MGS|max and selecting the image related to the greatest MGS|max. The method further includes modifying the set Set(i) of MGSs related to the selected image, and repeating the steps described above until a predetermined criterion selected from a group consisting of a number N of images and a score threshold is met.

Abstract: Methods for capturing and transmitting images by an in-vivo device comprise operating a pixel array in a superpixel readout mode to capture probe image, for example, according to a time interval. Concurrently to capturing of each probe image, the probe image is evaluated alone or in conjunction with other probe image(s), and if it is determined that no event of interest is detected by the last probe image, or by the last few probe images, the pixel array is operated in the superpixel readout mode and a subsequent probe image is captured. However, if it is determined that the last probe image, or the last few probe images, detected an event of interest, the pixel array is operated in a single pixel readout mode and a single normal image, or a series of normal image, is captured and transmitted, for example, to an external receiver.

Abstract: An optimization unit controls electrical currents of a set of electromagnets to generate a wanted maneuvering magnetic field pattern (MMP) for moving an in-vivo device in the GI system. The optimization unit may calculate a magnetic force and a magnetic field to maneuver the in-vivo device from a current location and/or orientation to a new location and/or orientation. The optimization unit may solve a magnetic force optimization problem with respect to the magnetic force in order to determine electrical currents suitable for generating the wanted MMP. The optimization unit may additionally or alternatively solve a minimum electrical power optimization problem with respect to the electrical power to be consumed by the electromagnets in order to recalculate or adjust the electrical currents. The optimization unit may solve one or more of the optimization problems while complying with a set of constraints associated with or derived from each type of optimization objective.