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: This disclosure describes how to identify objects in an augmented reality environment. More specifically, the various systems and methods described herein describe how an augmented reality device can recognize objects within a real world environment, determine where the object is located, and also identify the various surfaces of the object in real time or substantially real time.

Abstract: In certain aspects of the present disclosure, a computer-implemented method includes receiving a 3D imaging. The method includes generating 3D models based on the 3D imaging. The method includes generating, responsive to a pre-determined set of surgical steps, a finite number of 4D time deformation scenes for each pre-determined surgical step associated with the 3D models. The method includes displaying selectively interactive simulations based on the finite number of 4D time deformation scenes. Systems and machine-readable media are also provided.

Abstract: A method of identifying an object of interest can comprise obtaining first samples of an intensity distribution of one or more object of interest, obtaining second samples of an intensity distribution of confounder objects, transforming the first and second samples into an appropriate first space, performing dimension reduction on the transformed first and second samples, whereby the dimension reduction of the transformed first and second samples generates an object detector, transforming one or more of the digital images into the first space, performing dimension reduction on the transformed digital images, whereby the dimension reduction of the transformed digital images generates one or more reduced images, classifying one or more pixels of the one or more reduced images based on a comparison with the object detector, and identifying one or more objects of interest from the classified pixels.

Abstract: A method, a device and a computer-readable storage medium with instructions for processing sensor data. In a first step, camera images are taken by a camera. Additionally, 3D-checkpoints are detected by at least one 3D-sensor. Optionally, at least one of the camera images can be segmented. The camera images are then merged with the 3D-checkpoints by a data fusion circuit to form data of a virtual sensor. The resulting data are finally output for further processing.

Abstract: A system includes an intraoral scanner that generates a plurality of intraoral images of a dental site and a computing device. The computing device generates a first surface of a first region of the dental site based on a first intraoral image and generates a second surface of a second region of the dental site based on a second intraoral image. The computing device determines relative positions of the first surface and the second surface, wherein overlap between the first region of the dental site represented in the first intraoral image and the second region of the dental site represented the second intraoral image is insufficient for registration of the second intraoral image to the first intraoral image. The computing device outputs the first surface and the second surface having the relative positions to a display.

Abstract: This application relates to teaching applications of virtual reality technology, and provides a three-dimensional (3D) integrated teaching field system based on a flipped platform and a method for operating the same. The system includes a device deployment module, a teaching resource matching module, an acquisition and processing module and an edge computing module. The method includes spatial division of the 3D comprehensive teaching field system in an offline classroom, device deployment, edge computing, holographic display, data acquisition, motion positioning, and construction of a teaching interactive environment.

Abstract: The present disclosure provides a method and system for large-capacity image steganography and recovery based on an invertible neural networks. The method is intended to embed one or more hidden images into a single host image, and recover all the hidden images from a stego image. The method designs an image steganography model that supports bidirectional mapping. The model includes cascaded invertible modules containing a host branch and a hidden branch. A hidden image is embedded into a host image through forward mapping to form a stego image, and the host image and the hidden image are separated and recovered from the single stego image through reverse mapping.

Abstract: Systems and methods combine an input image with an edited image generated using a generator neural network to preserve detail from the original image. A computing system provides an input image to a machine learning model to generate a latent space representation of the input image. The system provides the latent space representation to a generator neural network to generate a generated image. The system generates multiple scale representations of the input image, as well as multiple scale representations of the generated image. The system generates a first combined image based on first scale representations of the images and a first value. The system generates a second combined image based on second scale representations of the images and a second value. The system blends the first combined image with the second combined image to generate an output image.

Abstract: A method for pancreatic mass diagnosis and patient management includes: receiving CT images of a pancreas of a patient, the pancreas of the patient including a mass; performing a segmentation process on the CT images of the pancreas and the mass to obtain a segmentation mask of the pancreas and the mass of the patient; performing a mask-to-mesh process on the segmentation mask of the pancreas and the mass of the patient to obtain a mesh model of the pancreas and the mass of the patient; performing a classification process on the mesh model of the pancreas and the mass of the patient to identify a type and a grade of a segmented pancreatic mass; and outputting updated CT images of the pancreas of the patient, the updated CT images including the segmented pancreatic mass highlighted thereon and the type and the grade of the segmented pancreatic mass annotated thereon.

Abstract: A method and system for classification of cells and particles in a biological sample using an automated image-based feature extraction and classification architecture. A method operates by applying a mask or series of masks to an image, extracting features from the unmasked portions of the image based on the content and location of colored pixels, selecting a subset of the extracted features, and mapping the subset of the extracted features into a classifier architecture. In a majority of cases, the first level model architecture provides an accurate identification of the cell or particle. In a minority of cases, the classification of the cell or particle requires a second level step requiring the use of numerical or categorical values from the first level in combination with a second level model.

Abstract: A focus following method based on a motion gravity center, a storage medium and a photographing system are provided. The focus following method includes the following steps: S1, acquiring video data captured by a camera within an initial time period; S2, acquiring video data with only a living object within the initial time period; S3, acquiring a motion gravity center image from the video data with only the living object according to a motion gravity center library; and S4, calculating an initial motion direction and an initial motion speed of the motion gravity center image within the initial time period. According to the present disclosure, the calculation amount is greatly reduced, the complex data is simplified, focus following based on the motion gravity center under poor hardware conditions can be can achieved, and requirements of low-cost and mass-production hardware can be satisfied.

Abstract: The disclosure provides an image reconstruction method for an edge device, an electronic device and a storage medium. The image reconstruction method includes: extracting low-level features from an input image of a first scale to generate first feature maps, the first feature maps having a second scale greater than the first scale as compared with the input image; extracting low-level features from the input image to generate second feature maps, the second feature maps having the second scale; generating mask maps based on the second feature maps; generating intermediate feature maps based on the mask maps and the first feature maps, the intermediate feature maps having the second scale; synthesizing a reconstructed image having the second scale based on the intermediate feature maps. This method facilitates to achieve a better image super-resolution reconstruction effect with lower resource consumption.

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: Provided are methods and apparatus for creating super-compressed map files. Using free and open-source software (FOSS), the tool create a super-compressed internally tiled Geo Tag Image File Format (TIFF) in a WGS84 datum (WGS84) similar in size to the original LizardTech's MrSID (SID) imagery from the National Geospatial-Intelligence Agency (NGA). Converting NGA data to WGS84 allows mapping systems like NASA Worldwind (WW) to eliminate the step of re-projecting on the fly from non-native projections, thus reducing processing time. The disclosed method includes removing all pure-black pixels by setting them to black+1, changing all near-black border pixels with values less than 15 to 0 (pure black), setting pure black values to “no-data,” compressing the image with a compression scheme, and translating the compressed image to JPEG and a YCbCr color space to achieve greater compression.

Abstract: Disclosed are various embodiments for optimizing cubic utilization when loading items into a loading space. A current loading configuration of the loading space can be determined according to image data obtained by 3D sensors. Item data (e.g., volume, mass, type, dimensions, etc.) can be determined for incoming items to be loaded into the loading space. The current loading configuration and the item data can be used to determine an item sequence and optimal placement location for the next item to be loaded such that a cubic efficiency of the loading space is maximized and amount of air gaps between items is minimized. The current loading configuration can further be used to determine if a sensing system or an item loading system needs to be repositioned. Whether the next item was placed in the optimal placement can also be verified based on subsequent image data obtained by the 3D sensors.

Abstract: An apparatus for assessing a hemodynamic property in a coronary vasculature and a corresponding method are provided in which diagnostic data of a vessel of interest is used to identify a first and second measurement position at which a first and a second value for a first hemodynamic property may be obtained whereby these first and second values are suitable to derive at least one diagnostic parameter indicative of a second hemodynamic 5 property that cannot or should not be measured directly.

Abstract: The image processing system acquires a foreground mask from a captured image acquired by capturing an object with an image capturing unit whose exposure value is set relatively higher or lower than that of another image capturing unit, acquires an inappropriate area mask by detecting an area whose exposure value is inappropriate in the captured image, and generates shape data representing a three-dimensional shape of the object based on the foreground mask and the inappropriate area mask.

Abstract: A computer system is disclosed comprising a processor arrangement communicatively coupled to a data storage arrangement storing a digital model of a section of a lumen system of a patient; and a communication module communicatively coupled to said processor arrangement and arranged to receive sensor data pertaining to an internal parameter of said lumen system from a sensor within said section of the lumen system. The processor arrangement is arranged to receive said sensor data from the communication module; retrieve said digital model from the data storage arrangement; simulate an actual physical condition of said lumen system by developing said digital model based on the received sensor data; and generate an output relating to said simulated actual physical condition for updating an electronic device. Also disclosed is a method of monitoring a patient with such a computer system, a computer program product for implementing such a method and a patient monitoring system.

Abstract: A method for one or more processors to select a plurality of documents. The one or more processors calculate a similarity between pairs of pages of respective documents of the plurality of documents. The one or more processors determine a document similarity value of the respective documents of the plurality of documents, based on a quantity of the pairs of pages of the respective document with a similarity calculated to be less than a predetermined threshold, and the one or more processors present the plurality of documents in a descending order, based on the document similarity value of the respective documents of the plurality of documents.