Abstract: Systems and methods for orthognathic surgical planning are described herein. An example computer-implemented method can include generating a composite three-dimensional (3D) model of a subject's skull, defining a primal reference frame for the composite 3D model, performing a cephalometric analysis on the composite 3D model to quantify at least one geometric property of the subject's skull, performing a virtual osteotomy to separate the composite 3D model into a plurality of segments, performing a surgical simulation using the osteotomized segments, and designing a surgical splint or template for the subject.

Abstract: An information processing apparatus (2000) displays, on a display apparatus (60), a first display (30) that represents a partial image (14) where an object contained therein was not recognized as a product. The information processing apparatus (2000) receives input for selecting one or more first displays (30). The information processing apparatus (2000), upon receiving a predetermined input from a user, ends receiving selection of a first display (30). The information processing apparatus (2000) stores, in a storage apparatus (120), product identification information input to a product information input area (54) and feature information based on a partial image(s) (14) corresponding to a selected first display(s) in association with each other.

Abstract: The invention provides systems, apparatus and methods for digital image processing providing enhanced display of and radiomics generated from images generated from x-ray and other medical imaging data. Such systems, apparatus and methods capture and use that data to identify distinct gradations, e.g., of grayscale within and beyond the spectrum of human vision, then delineate borders based on ranges of gradation, forming irregular multi-layer visual objects with delineated internal contouring and an outer boundary, and then enhance the delineated layers and superimpose the enhancing display over and/or determine radiomic measures of the corresponding areas of the original image, thereby revealing underlying morphology of masses previously obscured, hidden or “masked” from human vision.

Abstract: A method of plane tracking comprising: capturing by a camera a reference frame of a given plane from a first angle; capturing by the camera a destination frame of the given plane from a second angle different than the first angle; defining coordinates of matching points in the reference frame and the destination frame; calculating, using the first and second angles, first and second respective rotation transformations to a simulated plane parallel to the given plane; applying an affine transformation between the reference frame coordinate on the simulated plane and the destination frame coordinate on the simulated plane; and applying a projective transformation on the simulated plane destination frame coordinate to calculate the destination frame coordinate.

Abstract: The present invention involves orthopedic implants of small joints in human, in particular a truly patient-specific bone implanting system comprising the implant and surgical tools fabricated by additive manufacturing techniques based on the inputs conforming to each patient's anatomy and obtainable from a wide range of existing 3-dimensional imaging and image processing technologies, which offers a substantial progress in logistics, efficiency of surgical operation, and functionality of treated bones.

Abstract: Crosstalk mitigation among cameras in neighboring monitored workcells is achieved by computationally defining a noninterference scheme that respects the independent monitoring and operation of each workcell. The scheme may involve communication between adjacent cells to adjudicate non-interfering camera operation or system-wide mapping of interference risks and mitigation thereof. Mitigation strategies can involve time-division and/or frequency-division multiplexing.

Abstract: According to the invention, there are provided a system, a method and a computer program for producing an implant placing guide. In some embodiments, a method might include acquiring a three-dimensional intraoral image by a CT scan in a state where a guide tray filled with an impression material is inserted into an oral cavity of a patient and receiving implant planning information on the three-dimensional image. The method may continue by matching an image of the guide tray and the three-dimensional image by using marker information of the guide tray and locating a guide hole on the image of the guide tray. Next, the method may continue by generating an implant-placing-guide processing file by using the image of the guide tray in which the guide hole is located. According to the invention, a time for producing an implant placing guide is significantly shortened improving patient experience.

Abstract: Methods and an apparatuses for recognizing a text, recognition devices and storage media are provided, which belong to the field of text detections. A method includes: extracting, by the recognition device, a feature map of a to-be-recognized image, then determining segmentation information of a text region of the to-be-recognized image based on a preset segmentation network and the feature map, and then determining boundary key points in the text region based on the segmentation information, and then converting a text in the text region into a text with a target arrangement sequence based on the boundary key points and then inputting the text obtained by conversion into a preset recognition model for recognition processing.

Abstract: An approach is disclosed for visually identifying and/or pairing ride providers and passengers. The approach involves, for example, receiving location data indicating that a driver vehicle is within a proximity threshold of a passenger pickup location. The approach also involves initiating an activation of a camera of a passenger device to present live imagery on the passenger device. The approach further involves processing sensor data collected from one or more sensors of the passenger device to determine a rotation vector indicating a pointing direction of the passenger device. The approach also involves determining a new direction to point the passenger device to capture the driver vehicle in a field of view of the camera based on the rotation vector and the location data. The approach further involves providing output data for presenting a representation of the new direction in a user interface of the passenger device.

Abstract: A system and method for managing and tracking fishing/hunting rules and regulations is provided. The system generally comprises a global positioning system (GPS), a processor operably connected to the GPS, a power supply, a display operably connected to the processor, and a non-transitory computer-readable medium coupled to the processor and having instructions stored thereon. The system and method are designed to easily and conveniently compile and store information or data related to wildlife sports. The system may use this information to help a user comply with state and federal rules and regulations via the creation of registration strategies and via indicia.

Abstract: In some aspects, the described systems and methods provide for a method for training a statistical model to predict tissue characteristics for a pathology image. The method includes accessing annotated pathology images. Each of the images includes an annotation describing a tissue characteristic category for a portion of the image. A set of training patches and a corresponding set of annotations are defined using an annotated pathology image. Each of the training patches in the set includes values obtained from a respective subset of pixels in the annotated pathology image and is associated with a corresponding patch annotation determined based on an annotation associated with the respective subset of pixels. The statistical model is trained based on the set of training patches and the corresponding set of patch annotations. The trained statistical model is stored on at least one storage device.

Abstract: Disclosed is a micro-expression recognition method based on a multi-scale spatiotemporal feature neural network, in which spatial features and temporal features of micro-expression are obtained from micro-expression video frames, and combined together to form more robust micro-expression features, at the same time, since the micro-expression occurs in local areas of a face, active local areas of the face during occurrence of the micro-expression and an overall area of the face are combined together for micro-expression recognition.

Abstract: The present disclosure relates to a method for patient-specific optimization of imaging protocols. According to an embodiment, the present disclosure relates to a method for generating a patient-specific imaging protocol, comprising acquiring scout scan data, the scout scan data including scout scan information and scout scan parameters, generating a simulated image based on the acquired scout scan data, deriving a simulated dose map from the generated simulated image, determining image quality of the generated simulated image by applying machine learning to the generated simulated image, the neural network being trained to generate at least one probabilistic quality representation corresponding to at least one region of the generated simulated image, evaluating the determined image quality relative to a image quality threshold and the derived simulated dose map relative to a dosage threshold, optimizing.

Abstract: Aspects of the invention include a computer-implemented method including extracting a domain-specific object feature from a first image data, wherein the feature describes an object in the first image data. A domain-specific semantic meaning of text data is determined. The object feature is mapped to a portion of the text data, wherein the portion of the text data describes the object. A joint representation of the object and the portion of the text data is created. A second image data and a query directed towards an object in the second image data is received. An answer to the query is generated based on the joint representation.

Abstract: In one embodiment, a medical information processing apparatus includes processing circuitry configured to: perform processing using a trained model that is generated by machine learning with a plurality of training data; acquire first attribute data indicating an attribute of an object-to-be-trained related to the plurality of training data that are used for generating the trained model; acquire second attribute data indicating an attribute of an object-to-be-diagnosed; and perform the processing on input-data of the object-to-be-diagnosed based on goodness of fit that is an index indicating degree of matching between the first attribute data and the second attribute data.

Abstract: Certain aspects involve a machine-learning query system that uses a dual deep learning network to service queries and other requests. In one example, a machine-learning query system services a query received from a client computing system. A dual deep learning network included in the machine-learning query system matches an unstructured input data object, received from the client computing system, to an unstructured reference data object. The matching may include generating an input feature vector by an embedding subnetwork, based on the unstructured input data object. The matching may also include generating an output probability by a relationship subnetwork, based on the input feature vector and a relationship feature vector that is based on the unstructured reference data object. The machine-learning query system may transmit a responsive message to the client system.

Abstract: Systems and methods are disclosed for predicting healthy lumen radius and calculating a vessel lumen narrowing score. One method of identifying a lumen diameter of a patient's vasculature includes: receiving a data set including one or more lumen segmentations of known healthy vessel segments of a plurality of individuals; extracting one or more lumen features for each of the vessel segments; receiving a lumen segmentation of a patient's vasculature; determining a section of the patient's vasculature; and determining a healthy lumen diameter of the section of the patient's vasculature using the extracted one or more features for each of the known healthy vessel segments of the plurality of individuals.

Abstract: Systems, methods, and non-transitory computer readable media are provided for labeling depictions of objects within images. An image may be obtained. The image may include a depiction of an object. A user's marking of a set of dots within the image may be received. The set of dots may include one or more dots. The set of dots may be positioned within or near the depiction of the object. The depiction of the object within the image may be labeled based on the set of dots.

Abstract: Techniques for performing a prediction task using a multi-modal statistical model configured to receive input data from multiple modalities including input data from a first modality and input data from a second modality different from the first modality.

Abstract: Methods and systems for training computer-aided condition detection systems. One method includes receiving a plurality of images for a plurality of patients, some of the images including an annotation associated with a condition; iteratively applying a first deep learning network to each of the images to produce an attention map, a feature map, and an image-level probability of the condition for each of the images; iteratively applying a second deep learning network to each feature map produced by the first network to produce a plurality of outputs; training the first network based on the attention map produced for each image; and training the second network based on the output produced for each of the patients. The second network includes a plurality of convolution layers and a plurality of convolutional long short-term memory (LSTM) layers. Each of the outputs includes a patient-level probability of the condition for one of the patients.