Abstract: One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to a process to facilitate abnormal document self-discovery. A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components can comprise an object detection component that can generate a knowledge graph with vectors corresponding with nodes representative of a page layout of a document. Additionally, the computer executable components can comprise an evaluation component that can compare the vectors to identify whether an edge is present between corresponding vectors of the knowledge graph; an encoder component that can re-code the knowledge graph; and a comparison component that can compare a structure of the knowledge graph with one or more other knowledge graphs corresponding to one or more other documents to determine if the document is abnormal.

Abstract: An example operation may include one or more of generating a three-dimensional (3D) model of an object via execution of a machine learning model on one or more images of the object, capturing a plurality of snapshots of the 3D model of the object at different angles to generate a plurality of snapshot images of the object, fusing a feature into each of the plurality of snapshots to generate a plurality of fused snapshots of the 3D model of the object, and storing the plurality of fused snapshots of the 3D model of the object in memory.

Abstract: A display may have a pixel array such as a liquid crystal pixel array. The pixel array may be illuminated with backlight illumination from a direct-lit backlight unit. The backlight unit may include an array of light-emitting diodes (LEDs) on a printed circuit board. The display may have a notch to accommodate an input-output component. Reflective layers may be included in the notch. The backlight may include a color conversion layer with a property that varies as a function of position. The light-emitting diodes may be covered by a slab of encapsulant with recesses in an upper surface.

Abstract: A data processing apparatus configured to search for a combination of values of a plurality of state variables that minimizes or maximizes a value of an Ising-type evaluation function, when a change in a value of a first state variable is permitted, updating the value of the first state variable, updating a first local field based on a first weight value related to the first state variable, and updating a second local field based on a second weight value related to the first state variable, when the change in a value of the first auxiliary variable is permitted, updating the value of the first auxiliary variable, and updating the first local field based on a second weight value related to the first auxiliary variable.

Abstract: The present invention discloses the zonal trabecular femoral condylar component containing zirconium-niobium alloy on oxidation layer and its preparation method. The preparation method is as follows: using zirconium-niobium alloy powder as a raw material, conducting a 3D printing for one-piece molding, and obtaining intermediate products of the zonal trabecular femoral condylar component containing zirconium-niobium alloy on oxidation layer, after Sinter-HIP, cryogenic cooling and surface oxidation, the zonal trabecular femoral condylar component containing zirconium-niobium alloy on oxidation layer is prepared. Partial of the zonal trabecular femoral condylar component containing zirconium-niobium alloy on oxidation layer is provided with Zonal trabecula.

Abstract: A circular sign candidate extraction device includes: a memory; and a processor coupled to the memory, the processor being configured to perform processing, the processing including: detecting a circle from a captured image; specifying an annular region surrounded by the detected circle and a concentric circle, the concentric circle being a circle having a radius different from the detected circle; setting one or more pixels among pixels included in the annular region as determination pixels; and extracting a circular sign candidate from the detected circle in accordance with comparison between a color of the determination pixel and a predetermined color.

Abstract: An optimization apparatus of: performing a search for an optimal solution through iteration of processing configured to determine, by using a difference between a first energy value of an evaluation function in a first state and a second energy value of the evaluation function in a second state, whether to accept a state transition from the first state to the second state, and perform the state transition; and in the performing of the search for the state, storing the difference between the first and second energy values, and the respective values of the evaluation function in the second state, in a case where negation of the state transition is consecutively iterated a specific number of times, selecting one state from among the stored second states, based on the differences, and making the state transition from the first state to the selected one state.

Abstract: According to an aspect, a method includes receiving data about a patient, computing geometric characterization of one or more organs at risk proximate to a target volume of a patient or vice versa, and selecting relevant treatment knowledge and experience. The method also includes generating, based on the received data, computed geometric characterization, and available knowledge and experience, a first set of radiation treatment planning parameters that will lead to a high quality plan for the patient. Further, the method includes model-based prediction, based on the data, a second set or more of radiation treatment planning parameters that will lead to alternative achievable plans with different organ sparing objectives for treating the patient. The multiple sets for parameters can be used separately or in conjunction to generate treatment plans.

Abstract: Systems and methods for efficient and automatic determination of radiation beam configurations for patient-specific radiation therapy planning are disclosed. According to an aspect, a method includes receiving data based on patient information and geometric characterization of one or more organs at risk proximate to a target volume of a patient. The method includes determining automatically one or more radiation treatment beam configuration sets. Further, the method includes presenting the determined one or more radiation beam configuration sets via a user interface.

Abstract: A radiation treatment planning system can include a machine learning system that receives patient data, including an image scan (e.g., CT scan) and contour(s), a physician prescription, including planning target and dose, and device (radiation beam) data and outputs predicted fluence maps. The machine learning system includes at least two stages, where a stage of the at least two stages includes converting image scans from the patient data to projection images. A treatment planning system can receive the predicted fluence maps and generates treatment plans without performing inverse optimization.

Abstract: Systems and methods are provided for single isocenter radiotherapy of multiple targets. Conformal arc information may be used in a Conformal Arc Informed Volumetric Modulated Arc Therapy (CAVMAT) method that includes single isocenter radiotherapy of multiple targets where conformal multi-leaf collimator (MLC) trajectories may be used as the starting point for limited inverse optimization. Single isocenter radiotherapy of multiple targets may provide flexibility with less complex MLC trajectories, and fully block between targets with the MLC.

Abstract: Systems and methods are provided for using prior radiotherapy treatment machine parameter trajectory files to determine or predict the machine parameter trajectory at treatment delivery for a new radiotherapy plan, and to quantify the corresponding dosimetric effect of the difference between these machine parameters and the original radiotherapy plan. A pre-treatment quality assurance may thereby be generated that requires no extra beam-on time and provides preemptive insight into the plan quality. The system may include a multi-leaf collimator configured to deliver a treatment plan to a subject and configured to interact with the computer-based algorithm and/or any associated equipment used to perform the quality assurance tasks.

Abstract: An image identification apparatus includes: a memory; and a processor coupled to the memory, the processor being configured to perform processing, the processing including: acquiring a contour image where pixels indicating a contour of a subject are extracted from an input image; detecting pixels of 3 points or more over the contour from each of regions in the contour image, which are separated by a predetermined distance in a vertical direction or a horizontal direction; calculating, for each combination of pixels of every 2 points among the detected pixels, an intersection point of a perpendicular bisector of a line segment having 2 points as end points and a distance between the intersection point and one of the detected pixels; and identifying, from the input image, a circle having the intersection point as a center of the circle and the distance as a radius.

Abstract: A circular sign candidate extraction device includes: a memory; and a processor coupled to the memory, the processor being configured to perform processing, the processing including: detecting a circle from a captured image; specifying an annular region surrounded by the detected circle and a concentric circle, the concentric circle being a circle having a radius different from the detected circle; setting one or more pixels among pixels included in the annular region as determination pixels; and extracting a circular sign candidate from the detected circle in accordance with comparison between a color of the determination pixel and a predetermined color.

Abstract: Methods and associated reagents for assessing and resolving nucleic acid mixtures and/or mixed cell populations are disclosed herein. Some embodiments of the technology are directed to utilizing Duplex Sequencing for assessing and resolving nucleic acid mixtures (e.g., multichimeric mixtures, mixtures of nucleic acids from more than one source, etc.) in a sample and associated applications. Other embodiments are directed to detecting and quantifying a donor source of nucleic acid from a mixture.

Abstract: Systems and methods for automatic, customized radiation treatment plan generation for cancer are disclosed. According to an aspect, a method includes receiving data indicating anatomy information of a patient and radiation beam characteristics of a radiation therapy system. Further, the method includes determining energy levels for application of radiation beams to the patient.

Abstract: An image identification apparatus includes: a memory; and a processor coupled to the memory, the processor being configured to perform processing, the processing including: acquiring a contour image where pixels indicating a contour of a subject are extracted from an input image; detecting pixels of 3 points or more over the contour from each of regions in the contour image, which are separated by a predetermined distance in a vertical direction or a horizontal direction; calculating, for each combination of pixels of every 2 points among the detected pixels, an intersection point of a perpendicular bisector of a line segment having 2 points as end points and a distance between the intersection point and one of the detected pixels; and identifying, from the input image, a circle having the intersection point as a center of the circle and the distance as a radius.

Abstract: Systems and methods for radiation treatment planner training based on knowledge data and trainee input of planning actions are disclosed. According to an aspect, a method includes receiving case data including anatomical and/or geometric characterization data of a target volume and one or more organs at risk. Further, the method includes presenting, via a user interface, the case data to a trainee. The method also includes receiving input indicating an action to apply to the case. The input indicating parameters for generating a treatment plan that applies radiation dose to the target volume and one or more parameters for constraining radiation to the one or more organs at risk. The method includes applying training models to the action and the case data to generate analysis data of at least one parameter of the action. The method includes presenting the analysis data of the at least one parameter of the action.

Abstract: An apparatus includes a programmable circuit that configures circuits for executing tasks. The apparatus estimates an execution time-period required for executing a first task by first circuits configured in the programmable circuit, and determines a configuration number indicating a number of second circuits that are to be configured, in the programmable circuit, for executing a second task to be executed after the first task, based on the execution time-period and a configuration time-period required for configuring the configuration number of the second circuits in the programmable circuit. The apparatus causes the programmable circuit to configure, during execution of the first task, the configuration number of the second circuits, and adjusts the configuration number, based on a relationship between a time at which the first task is completed and a time at which configuration of the configuration number of the second circuits in the programmable circuit is completed.

Abstract: Systems and methods for automatic, customized radiation treatment plan generation for cancer are disclosed. According to an aspect, a method includes receiving data indicating anatomy information of a patient and radiation beam characteristics of a radiation therapy system. Further, the method includes determining energy levels for application of radiation beams to the patient.