Abstract: The invention provides a method for cargo sorting, configured to control an end effector with a package placement platform to sort the cargo, and the method includes: moving the package placement platform to a package obtaining position and obtaining the cargo to be sorted that enters into the package placement platform; moving the package placement platform to a package storage location; and exerting a first force to push the cargo into a package storage unit. With the help of the package placement platform, the method of the invention can receive the packages of different types or different sizes or different material so as to sort and transport all kinds of packages.

Abstract: The present disclosure provides a touch screen sensor and a touch screen with the touch screen sensor. The touch screen sensor includes a plurality of grid cells, wherein the plurality of grid cells are connected to each other to form the touch screen sensor; and each grid cell includes a plurality of metal electrode wires arranged in an intersecting manner, the plurality of grid cells at least form a three-wire intersection mode at part of intersection points, and a plurality of identical grid cells are repeatedly connected or different grid cells are arranged in the intersecting manner to form a touch electrode. In some embodiments of the present disclosure, at least part of the intersection points of a four-wire intersection mode of the grid cells are adjusted and arranged to be intersection points of the three-wire intersection mode.

Abstract: In part, the disclosure relates to methods, and systems suitable for evaluating image data from a patient on a real time or substantially real time basis using machine learning (ML) methods and systems. Systems and methods for improving diagnostic tools for end users such as cardiologists and imaging specialists using machine learning techniques applied to specific problems associated with intravascular images that have polar representations. Further, given the use of rotating probes to obtain image data for OCT, IVUS, and other imaging data, dealing with the two coordinate systems associated therewith creates challenges. The present disclosure addresses these and numerous other challenges relating to solving the problem of quickly imaging and diagnosis a patient such that stenting and other procedures may be applied during a single session in the cath lab.

Abstract: The disclosure relates to methods of providing live x-ray images such as fluoroscopic images in combination with reference information co-registered angiography frames that are motion corrected in real time. In part, the disclosure describes an improvement on the existing workflow where the user must remember where the vessel features from OCT are and use a reference frame to estimate the location of desired stent placement. Disclosed herein are methods to correlate the live imaging feed and the reference angiography image such that the user may dynamically zoom and pan the live imaging feed and the reference angiography image.

Abstract: In part, the disclosure relates to methods, and systems suitable for evaluating image data from a patient on a real time or substantially real time basis using machine learning (ML) methods and systems. Systems and methods for improving diagnostic tools for end users such as cardiologists and imaging specialists using machine learning techniques applied to specific problems associated with intravascular images that have polar representations. Further, given the use of rotating probes to obtain image data for OCT, IVUS, and other imaging data, dealing with the two coordinate systems associated therewith creates challenges. The present disclosure addresses these and numerous other challenges relating to solving the problem of quickly imaging and diagnosis a patient such that stenting and other procedures may be applied during a single session in the cath lab.

Abstract: In part, the disclosure relates to methods, and systems suitable for evaluating image data from a patient on a real time or substantially real time basis using machine learning (ML) methods and systems. Systems and methods for improving diagnostic tools for end users such as cardiologists and imaging specialists using machine learning techniques applied to specific problems associated with intravascular images that have polar representations. Further, given the use of rotating probes to obtain image data for OCT, IVUS, and other imaging data, dealing with the two coordinate systems associated therewith creates challenges. The present disclosure addresses these and numerous other challenges relating to solving the problem of quickly imaging and diagnosis a patient such that stenting and other procedures may be applied during a single session in the cath lab.

Abstract: Systems and methods are disclosed for identifying features of a blood vessel using extravascular and intravascular images in order to estimate a virtual flow reserve (VFR) of the imaged blood vessel. Aspects of the disclosure include using extravascular images to estimate the size of the blood vessel in regions that have not been intravascularly imaged. The VFR estimation may be based on a resistance model that incorporates both the intravascular image data and the estimated blood vessel size. In other aspects, multiangled extravascular images are captured and analyzed in order to identify the size and orientation of branch vessels.

Abstract: Systems and methods to analyzes images of lateral flow assays are disclosed herein. An example image analysis system includes processor circuitry to (a) determine whether a format of an image of a lateral flow assay device satisfies a format threshold, (b) in response to determining the format of the image satisfies the format threshold, determine whether the lateral flow assay device in the image is authentic, (c) in response to determining the lateral flow assay device is authentic, determine whether a position of the lateral flow assay device in the image satisfies a position threshold, (d) in response to determining the position of the lateral flow assay device satisfies the position threshold, analyze the image to determine the result of the diagnostic test, and (e) abort the sequence of the operations during performance of the sequence of operations at the time any one of operations fails.

Abstract: In part, the disclosure relates to methods, and systems suitable for evaluating image data from a patient on a real time or substantially real time basis using machine learning (ML) methods and systems. Systems and methods for improving diagnostic tools for end users such as cardiologists and imaging specialists using machine learning techniques applied to specific problems associated with intravascular images that have polar representations. Further, given the use of rotating probes to obtain image data for OCT, IVUS, and other imaging data, dealing with the two coordinate systems associated therewith creates challenges. The present disclosure addresses these and numerous other challenges relating to solving the problem of quickly imaging and diagnosis a patient such that stenting and other procedures may be applied during a single session in the cath lab.

Abstract: In part, the disclosure relates to methods, and systems suitable for evaluating image data from a patient on a real time or substantially real time basis using machine learning (ML) methods and systems. Systems and methods for improving diagnostic tools for end users such as cardiologists and imaging specialists using machine learning techniques applied to specific problems associated with intravascular images that have polar representations. Further, given the use of rotating probes to obtain image data for OCT, IVUS, and other imaging data, dealing with the two coordinate systems associated therewith creates challenges. The present disclosure addresses these and numerous other challenges relating to solving the problem of quickly imaging and diagnosis a patient such that stenting and other procedures may be applied during a single session in the cath lab.

Abstract: In part, the disclosure relates to methods, and systems suitable for evaluating image data from a patient on a real time or substantially real time basis using machine learning (ML) methods and systems. Systems and methods for improving diagnostic tools for end users such as cardiologists and imaging specialists using machine learning techniques applied to specific problems associated with intravascular images that have polar representations. Further, given the use of rotating probes to obtain image data for OCT, IVUS, and other imaging data, dealing with the two coordinate systems associated therewith creates challenges. The present disclosure addresses these and numerous other challenges relating to solving the problem of quickly imaging and diagnosis a patient such that stenting and other procedures may be applied during a single session in the cath lab.