Abstract: Based on information about a vehicle, the information can be projected and displayed onto a road surface or the like. An image projection apparatus, which projects an image, includes an acquisition unit that acquires the information about the vehicle, and an image projection unit that projects the image based on the information acquired by the acquisition unit.

Abstract: The present disclosure relates to methods and systems for obtaining image information of an organism including a set of optical data; calculating a growth index based on the set of optical data; and calculating an anticipated harvest time based on the growth index, where the image information includes at least one of: (a) visible image data obtained from an image sensor and non-visible image data obtained from the image sensor, and (b) a set of image data from at least two image capture devices, where the at least two image capture devices capture the set of image data from at least two positions.

Abstract: An imagery processing system determines alternative pixel color values for pixels of captured imagery where the alternative pixel color values are obtained from alternative sources. A main imagery capture device, such as a camera, captures main imagery such as still images and/or video sequences, of a live action scene. Alternative devices capture imagery of the live action scene, in some spectra and form, and that alternative imagery is processed to provide user-selectable alternatives for pixel ranges from the main imagery.

Abstract: There is provided a method of processing 2D ultrasound images for computing clinical parameter(s) of a right ventricle (RV), comprising: selecting one 2D ultrasound image of 2D ultrasound images depicting the RV, interpolating an inner contour of an endocardial border of the RV for the selected 2D image, tracking the interpolated inner contour obtained for the one 2D ultrasound image over the 2D images over cardiac cycle(s), computing a RV area of the RV for each respective 2D image according to the tracked interpolated inner contour, identifying a first 2D image depicting an end-diastole (ED) state according to a maximal value of the RV area for the 2D images, and a second 2D US image depicting an end-systole (ES) state according to minimal value of the RV area for the 2D images, and computing clinical parameter(s) of the RV according to the identified first and second 2D images.

Abstract: The image processing device includes a voxel extractor, a learner, and a predictor. The voxel extractor extracts a target voxel and neighboring voxels adjacent to the target voxel from a 3D image. The learner generates vectors corresponding to the target voxel and the neighboring voxels, respectively, generates vector weights corresponding to each of the vectors, based on the vectors and a parameter group, and adjusts the parameter group, based on an analysis result of the target voxel generated by applying the vector weights to the vectors. The predictor generates vectors corresponding to the target voxel and the neighboring voxels, respectively, generates correlation weights among the vectors by applying a parameter group to the vectors, generates vector weights corresponding to each of the vectors by applying the correlation weights to the vectors, and generates an analysis result of the target voxel by applying the vector weights to the vectors.

Abstract: A method for visualizing tissue of a subject includes receiving a first series of first imaging modality frames generated by imaging a region of tissue of the subject, and a first series of second imaging modality frames generated by imaging the region of tissue; displaying the first series of first imaging modality frames in combination with the first series of second imaging modality frames; storing a plurality of first imaging modality frames and a plurality of second imaging modality frames of the first series of second imaging modality frames in a memory; receiving a second series of first imaging modality frames generated by imaging the region of tissue; and displaying the second series of first imaging modality frames in combination with one or more of the second imaging modality frames of the first series of second imaging modality frames stored in the memory for visualizing the region of tissue.

Abstract: An apparatus includes: an acquisition circuit; and a processing circuit configured to: acquire volume data; set a model representing a tissue included in the volume data; set a first view for visualizing the volume data and a position of a target in the model; acquire first operation information for deforming the model; calculate change in the position and an orientation of the target due to deformation of the model, based on the first operation information; calculate, using the calculated change in the position and the orientation of the target, a second view such that the position and the orientation of the target after the change with respect to the first view and the position and the orientation of the target before the change with respect to the second view become equal to each other; and visualize the volume data based on the second view.

Abstract: A system for visibility enhancement for a motor vehicle assistant system for warning the driver of hazardous situations due to at least one object being located within a critical range defined relative to the motor vehicle includes at least a first sensor means comprising a camera installed in a rear view equipment of the motor vehicle adapted to record at least one image, and an image processing means adapted to receive a first input signal from the first sensor means containing the at least one image and a second input signal containing at least one position profile of the at least one object located within the critical range, and manipulate the at least one image to generate a contrast manipulated image. A corresponding method of visibility enhancement is also described.

Abstract: Example image processing methods, apparatus/systems and articles of manufacture are disclosed herein. An example apparatus includes an image recognition application to identify matches between stored patterns and objects detected in a shelf image, where the shelf image has a shelf image scale estimate. The example apparatus further includes a scale corrector to calculate deviation values between sizes of (A) a first set of the objects detected in the shelf image and (B) a first set of the stored patterns matched with the first set of the objects and reduce an error of the shelf image scale estimate by calculating a scale correction value for the shelf image scale estimate based on the deviation values.

Abstract: Provided in accordance with the present disclosure are systems and methods for identifying a percutaneous tool in image data. An exemplary method includes receiving image data of at least a portion of a patient's body, identifying an entry point of a percutaneous tool through the patient's skin in the image data, analyzing a portion of the image data including the entry point of the percutaneous tool through that patient's skin to identify a portion of the percutaneous tool inserted through the patient's skin, determining a trajectory of the percutaneous tool based on the identified portion of the percutaneous tool inserted through the patient's skin, identifying a remaining portion of the percutaneous tool in the image data based on the identified entry point and the determined trajectory of the percutaneous tool, and displaying the identified portions of the percutaneous tool on the image data.

Abstract: A method for using an assembled three-dimensional image to construct a three-dimensional model for determining a path through a lumen network to a target. The three-dimensional model is automatically registered to an actual location of a probe by tracking and recording the positions of the probe and continually adjusting the registration between the model and a display of the probe position. The registration algorithm becomes dynamic (elastic) as the probe approaches smaller lumens in the periphery of the network where movement has a bigger impact on the registration between the model and the probe display.

Abstract: Example implementations are directed to methods and systems for individualized multimedia navigation and control including receiving metadata for a piece of digital content, where the metadata comprises a primary image and text that is used to describes the digital content; analyzing the primary image to detect one or more objects; selecting one or more secondary images corresponding to each detected object; and generating a data structure for the digital content comprising the one or more secondary images, where the digital content is described by a preferred secondary image.

Abstract: A computer-implemented method of processing a digital dental impression includes determining one or more first digital surface regions visible from a first side of the digital dental impression along an occlusion axis and one or more second digital surface regions visible from a second side of the digital dental impression along the occlusion axis, segmenting the digital dental impression into one or more digital segments and determining the one or more digital segments as a first digital segment or a second digital segment based on the majority of digital surface regions in the one or more digital segments.

Abstract: Input coordinates identify a tile on the globe and a biome is identified for each pixel of the tile. We choose a random segmentation mask of the corresponding biome for the tile. Every segment of the mask carries a unique identifier and access to a random value via a corner reference. These parameters ensure that (when executed in parallel) each pixel with the same identifier and random value is handled the same way. For each pixel of the tile, using the selected mask, we identify the segment corresponding to that pixel, we retrieve a color variation for that pixel based upon the segment identifier and the random value. We thus choose a color variation for each segment of a segmentation mask. Pixels in the same segment are treated the same way. Instead of a color variation for flat areas (crop fields) we choose a density variation for regions like forests.

Abstract: Systems and methods are described for generating a three-dimensional track a ball in a gaming environment from a single camera. In some examples, an input video including frames of a ball moving in a gaming environment recorded by a camera may be obtained, along with a camera projection matrix associated with at least one frame that maps a two-dimensional pixel space representation to a three-dimensional representation of the gaming environment. Candidate two-dimensional image locations of the ball across the plurality of frames may be identified using a neural network or a computer vision algorithm. An optimization algorithm may be performed that uses a 3D ball physics model, the camera projection matrix and a subset of the candidate two-dimensional image locations of the ball to generate a three-dimensional track of the ball in the gaming environment. The three-dimensional track of the ball may then be provided to a user device.

Abstract: One example method for detecting phases of a surgical procedure via video processing includes accessing a video of the surgical procedure and dividing the video into one or more blocks, each of the blocks containing one or more video frames. For each of the blocks, the method includes applying a prediction model on the video frames of the respective block to obtain a phase prediction for each of the video frames. The prediction model is configured to predict, for an input video frame, one of the plurality of phases of the surgical procedure. The method further includes generating an aggregated phase prediction for the respective block by aggregating the phase predictions of the video frames, and modifying the video of the surgical procedure to include an indication of a predicted phase of the respective block based on the aggregated phase prediction.

Abstract: Patient specific implant technology, in which an outline representation of a portion of an outer surface of a periphery of a bone volume is determined and the outline representation is used in operations related to implant matching. In addition, an instrument may be made to match a perimeter shape of a Patient Specific Knee Implant with features for locating holes in a distal femur such that posts or lugs in a femoral implant locate the femoral implant centered medial-laterally within an acceptable degree of precision to prevent overhang of either the side of the femoral implant over the perimeter of the distal femur bone resections. Further, a two-dimensional outline representation may be segmented into segments that correspond to resection cuts used in fitting an implant on a portion of a bone and operations related to implant matching may be performed based on the segments.

Abstract: The present disclosure relates to methods and systems for obtaining image information of an organism including a set of optical data; calculating a growth index based on the set of optical data; and calculating an anticipated harvest time based on the growth index, where the image information includes at least one of: (a) visible image data obtained from an image sensor and non-visible image data obtained from the image sensor, and (b) a set of image data from at least two image capture devices, where the at least two image capture devices capture the set of image data from at least two positions.

Abstract: A medical device monitoring system and method extract information from screen images from medical device controllers, with a single OCR process invocation per screen image, despite critical information appearing in different screen locations, depending on which medical device controller's screen image is processed. For example, different software versions of the medical device controllers might display the same type of information in different screen locations. Copies of the critical screen information, one copy from each different screen location, are made in a mosaic image, and then the mosaic image is OCR processed to produce text results. Text is selectively extracted from the OCR text results, depending on contents of a selector field on the screen image, such as a software version number or a heart pump model identifier.

Abstract: A method for preventing wrong-patient errors includes receiving a selection of a current imaging subject. The current imaging subject is selected for a current image acquisition session comprising capturing one or more current images of the current imaging subject utilizing at least a first image sensor system of a first imaging modality. The method includes accessing one or more previous images of a previous imaging subject. The one or more previous images depict the previous imaging subject according to at least a second imaging modality that is different from the first imaging modality. The method includes presenting the one or more previous images on a display system and, in response to determining that the previous imaging subject matches the current imaging subject based upon the one or more previous images, performing the current image acquisition session.