Abstract: An image processing apparatus for evaluating cardiac images and a ventricular status identification method are provided. In the method, a region of interest (ROI) is determined from multiple target images, a variation in grayscale values of multiple pixels in the ROIs of each target image is determined, and one or more representative images are obtained according to the variation in the grayscale values. The target image is related to the pixels within an endocardial contour of a left ventricle. A boundary of the ROI is approximately located at two sides of a bottom of the endocardial contour. The ROI corresponds to a mitral valve. The variation in the grayscale values is related to a motion of the mitral valve. The representative image is for evaluating a status of the left ventricle.

Abstract: An object recognition method includes generating a cluster at a fixed period by clustering distance measurement points acquired from an object detection sensor, mapping the cluster to an image captured by an imaging means, setting a region on the image to which the cluster is mapped as a processing region, extracting a feature point from the image in the set processing region, calculating a movement speed of the extracted feature point, and determining whether clusters at different time points are clusters of an identical object based on a difference between positions of two feature points corresponding to the clusters at the different time points and a difference between movement speeds of the two feature points corresponding to the clusters at the different time points.

Abstract: A system and method for determining the locations and types of objects in a plurality of videos. The method comprises pairing each video with one or more sentences describing the activity or activities in which those objects participate in the associated video, wherein no use is made of a pretrained object detector. The object locations are specified as rectangles, the object types are specified as nouns, and sentences describe the relative positions and motions of the objects in the videos referred to by the nouns in the sentences. The relative positions and motions of the objects in the video are described by a conjunction of predicates constructed to represent the activity described by the sentences associated with the videos.

Abstract: A method for medical imaging may include obtaining a plurality of successive images of a region of interest (ROI) including at least a portion of an object's heart. The plurality of successive images may be based on imaging data acquired from the ROI by a scanner without electrocardiography (ECG) gating. The plurality of successive images may be related to one or more cardiac cycles of the object's heart. The method may also include automatically determining, in the plurality of successive images, target images that correspond to at least one of the one or more cardiac cycles of the object's heart.

Abstract: Methods and apparatus for providing attribute-based search of media assets such as video and audio assets, and associated augmented reality functions including dynamic provision of relevant secondary content relating to the identified attribute(s). In one embodiment, media or content assets are ingested into a processing system and processed according to one or more attribute detection, identification, and characterization algorithms. Attributes detected may include for example the presence of tangible items such as clothing or chattels, particular persons such as celebrities, and/or certain contexts such as sporting activities and musical performances, as rendered within the media asset. In one implementation, the characterized assets are provided a unique ID, and stored so as to permit cross-correlation based on, e.g., the identified and characterized attributes. Secondary content (e.g.

Abstract: Systems and methods reconstruct an image of a subject or object by performing an iterative reconstruction method to produce a plurality of intermediate images and the image of the subject, and transforming at least one selected intermediate image from the plurality of intermediate images using a quasi-projection operator. The quasi-projection operator includes a deep-learning model configured to map the at least one selected intermediate image to at least one regularized intermediate image. In addition, systems and methods for training the deep-learning model using a training data set that includes a plurality of training images and a plurality of corresponding training object images is disclosed.

Abstract: Disclosed are image based counting systems and methods. Image based counting systems and methods employ one or more imaging devices (e.g., one or more color cameras) and one or more illumination devices (e.g., one or more illumination sources to provide variable and/or dynamic lighting). In some examples, the image based counting system provides illumination to a tray upon which one or more items (e.g., pills) are placed. The illuminated items are then imaged by the one or more imaging devices based on one or more imaging techniques or processes to determine and/or present information associated with one or more properties of the item.

Abstract: In an aspect, a system for using artificial intelligence to evaluate, correct, and monitor user attentiveness includes a forward-facing camera, the forward-facing camera configured to capture a video feed of a field of vision on a digital screen, at least a user alert mechanism configured to output a directional alert to a user, a processing unit in communication with the forward-facing camera and the at least a user alert mechanism, a screen location to spatial location map operating on the processing unit, and a motion detection analyzer operating on the processing unit, the motion detection analyzer designed and configured to detect, on the digital screen, a rapid parameter change, determine a screen location on the digital screen of the rapid parameter change, retrieve, from the screen location to spatial location map, a spatial location based on the screen location, and generate, using the spatial location, the directional alert.

Abstract: A method of generating a correction plan for correcting a deformed bone includes inputting to a computer system a first image of the deformed bone in a first plane and inputting to the computer system a second image of the deformed bone in a second plane. Image processing techniques are employed to identify a plurality of anatomical landmarks of the deformed bone in the first image. The first image of the deformed bone is displayed on a display device. A graphical of the deformed bone is autonomously generated and graphically overlaid on the first image of the deformed bone on the display device, the graphical template including a plurality of lines, each line connected at each end to a landmark point corresponding to one of the anatomical landmarks. A model of the deformed bone may be autonomously generated based on the graphical template.

Abstract: According to example embodiments, an Image View Aggregator identifies a frontal view of an item within an image. The Image View Aggregator identifies at least one reflection view of the item within the image. Each reflection view of the item having been captured off a corresponding reflective physical surface. The Image View Aggregator extracts the frontal view of the item and each reflection view of the item from the image. The Image View Aggregator generates a representation of the item based at least on the extracted frontal view of the item and each extracted reflection view of the item.

Abstract: The present invention relates to the field of medical monitoring, and in particular non-contact, video-based monitoring of pulse rate, respiration rate, motion, and oxygen saturation. Systems and methods are described for capturing images of a patient, producing intensity signals from the images, filtering those signals to focus on a physiologic component, and measuring a vital sign from the filtered signals. Examples include flood fill methods and skin tone filtering methods.

Abstract: The present disclosure relates to the field of medical monitoring, and, in particular, to non-contact detecting and monitoring of patient breathing. Systems, methods, and computer readable media are described for calculating a change in depth of regions in one or more regions of interest (ROI's) on a patient and assigning one or more visual indicators to the regions based on the calculated changes in depth of the regions over time. In some embodiments, one or more breathing parameter signals corresponding to the regions can be generated and/or analyzed. In these and other embodiments, the one or more visual indicators can be displayed overlaid onto the regions in real-time. In these and still other embodiments, the systems, methods, and/or computer readable media (i) can display one or more generated breathing parameter signals in real-time and/or (ii) can trigger an alert and/or an alarm when a breathing abnormality is detected.

Abstract: Modifications are performed to cause a style of an image to match a different style. A first image is accessed, where the first image has the first style. A second image is also accessed, where the second image has a second style. Subsequent to a deep neural network (DNN) learning these styles, a copy of the first image is fed as input to the DNN. The DNN modifies the first image copy by transitioning the first image copy from being of the first style to subsequently being of the second style. As a consequence, a modified style of the transitioned first image copy bilaterally matches the second style.

Abstract: Apparatus for plotting pathological diagnoses on anatomical diagrams is provided. The apparatus may include a mapping tool. The mapping tool may identify a plurality of biopsy marker records including a received criterion. The mapping tool may identify a body part image associated with a body part image ID. The mapping tool may section the body part image into a first quadrant and a second quadrant. The mapping tool may loop through the plurality of biopsy marker records to identify an X,Y coordinate associated with each of the plurality of biopsy marker records. For each X,Y coordinate identifying a location within the first quadrant, the mapping tool may iteratively tally a first count for the first quadrant. For each X,Y coordinate identifying a location within the second quadrant, the mapping tool may iteratively tally a second count for the second quadrant.

Abstract: There is provided a method for measuring anatomical features of a body, comprising obtaining a video having a plurality of frames; analyzing each frame of the video to detect the position of each anatomical feature; if necessary, calculating the distance travelled between frames of an anatomical feature using a predetermined reference object within the video (e.g., the true length between one's knee and hip); and if necessary, using the raw video and extracted features to predict a biomechanical output, and/or calculating summary metrics from the aggregate data from the video.

Abstract: TOOL TRACKING A system for determining the location of a toolpiece, wherein: the toolpiece is carried by a tool and the tool comprises an imaging device for capturing images of the environment around the tool; and the system comprises an image processor communicatively coupled to the imaging device for receiving images therefrom and having access to one or more reference images of an expected environment, the image processor being configured to compare an image captured by the imaging device with at least one reference image to identify a match therebetween and to determine in dependence on characteristics of that match the location of the toolpiece.

Abstract: Techniques described herein may involve audio settings based on an environment. An example implementation may involve a playback device playing back first audio content and during playback of at least a portion of the first audio content, detecting, via the at least one microphone, an audio signal. At least a portion of the detected audio signal may include a reflection of the first audio content played back by the playback device. The playback device may determine an equalization setting based on at least the determined one or more reflection characteristics and apply the determined equalization setting during playback of second audio content.

Abstract: Provided is a generation unit that generates an identification region map indicating whether or not each divided object data is visible from each position in a three-dimensional space by using information regarding orientation of a normal vector dividing an object in the three-dimensional space and information regarding an outline of the object.

Abstract: An excrement judgement system according to the embodiment including: an acquisition unit that acquires image information on an image in which excrement excreted in a defecation action per time is captured; a determination unit that determines properties of a plurality of stools included in the image information and stool amounts corresponding to the properties of the plurality of stools; and an outputting unit that associates the properties of the plurality of stools and the stool amounts corresponding to the properties of the plurality of stools that are determined by the determination unit, and outputs the associated properties and stool amounts to a device to be displayed.

Abstract: Soundfield signals such as e.g. Ambisonics carry a representation of a desired sound field. The Ambisonics format is based on spherical harmonic decomposition of the soundfield, and Higher Order Ambisonics (HOA) uses spherical harmonics of at least 2nd order. However, commonly used loudspeaker setups are irregular and lead to problems in decoder design. A method for improved decoding an audio soundfield representation for audio playback comprises calculating a panning function (W) using a geometrical method based on the positions of a plurality of loudspeakers and a plurality of source directions, calculating a mode matrix (?) from the loudspeaker positions, calculating a pseudo-inverse mode matrix (?+) and decoding the audio soundfield representation. The decoding is based on a decode matrix (D) that is obtained from the panning function (W) and the pseudo-inverse mode matrix (?+).