Systems and methods are disclosed for identifying formerly conjoined pieces of tissue in a specimen, comprising receiving one or more digital images associated with a pathology specimen, identifying a plurality of pieces of tissue by applying an instance segmentation system to the one or more digital images, the instance segmentation system having been generated by processing a plurality of training images, determining, using the instance segmentation system, a prediction of whether any of the plurality of pieces of tissue were formerly conjoined, and outputting at least one instance segmentation to a digital storage device and/or display, the instance segmentation comprising an indication of whether any of the plurality of pieces of tissue were formerly conjoined.

A method for tracking an object in an image sequence with at least a first image and a second image includes the steps of: identifying a plurality of objects in the first image and a plurality of objects in the second image; determining matching probability of an object in the second image with an object in the first image, based on relative positional relationships between the plurality of objects in the first image and relative positional relationships between the plurality of objects in the second image; and determining, based on the determined matching probability, a matching result relating to whether the object in the second image matches with the object in the first image. A match indicates that the object in the second image corresponds with or originates from the corresponding object in the first image.

In an approach for propagating labels of objects in an image, a processor receives the image. A processor performs a normalization of the image. A processor runs the image through a pre-trained object detector. A processor receives a set of detected objects from the pre-trained object detector. A processor determines a width dimension and a height dimension of a bounding box for each detected object of the set of detected objects. A processor propagates a label for each instance of each detected object in the image with the respective bounding box using prior geometric knowledge of bounding box placement. A processor inverses the normalization of the labeled image. A processor outputs the labeled image.

In an approach for propagating labels of objects in an image, a processor receives the image. A processor performs a normalization of the image. A processor runs the image through a pre-trained object detector. A processor receives a set of detected objects from the pre-trained object detector. A processor determines a width dimension and a height dimension of a bounding box for each detected object of the set of detected objects. A processor propagates a label for each instance of each detected object in the image with the respective bounding box using prior geometric knowledge of bounding box placement. A processor inverses the normalization of the labeled image. A processor outputs the labeled image.

A method, computer system, and a computer-readable medium for registering one or more structures to a desired orientation for planning and guidance for surgery is provided. The method includes in a preoperative stage, obtaining one or more 3D models of one or more structures from one or more CT images using an image processing segmentation technique or a manual segmentation technique; in the preoperative stage, registering the one or more structures to a template that is adapted to an alternating registration for a patient-specific shape and pose for a desired reduction and corresponding reduction transformations; in an intraoperative stage, mapping the one or more structures to one or more radiographs via a 3D-2D registration that iteratively optimizes a similarity metric between acquired and simulated radiographs; and in the intraoperative stage, providing an output that is representative of a radiograph or a 3D tomographic representation to provide guidance to a user.

A method, computer system, and a computer-readable medium for registering one or more structures to a desired orientation for planning and guidance for surgery is provided. The method includes in a preoperative stage, obtaining one or more 3D models of one or more structures from one or more CT images using an image processing segmentation technique or a manual segmentation technique; in the preoperative stage, registering the one or more structures to a template that is adapted to an alternating registration for a patient-specific shape and pose for a desired reduction and corresponding reduction transformations; in an intraoperative stage, mapping the one or more structures to one or more radiographs via a 3D-2D registration that iteratively optimizes a similarity metric between acquired and simulated radiographs; and in the intraoperative stage, providing an output that is representative of a radiograph or a 3D tomographic representation to provide guidance to a user.

The present invention addresses the problem of providing a technique for determining the authenticity of a product without requiring a special device such as an integrated circuit (IC) tag. A means for solving this problem according to the invention is characterized by determining the authenticity of a target product on the basis of the validity of the association between the body of the product and a surface-treated component that is mounted to the body and that has been validated.

The present invention addresses the problem of providing a technique for determining the authenticity of a product without requiring a special device such as an integrated circuit (IC) tag. A means for solving this problem according to the invention is characterized by determining the authenticity of a target product on the basis of the validity of the association between the body of the product and a surface-treated component that is mounted to the body and that has been validated.

The present invention is to incorporate a novel two-step image registration algorithm that can achieve sub-pixel accuracy in order to provide a method and system that can significantly improve the remote monitoring performance of coral reefs and volcanoes using a future NASA remote imager known as HyspIRI, by increasing the spatial and temporal resolution of remote sensing data from multiple satellites. Our invention focuses on change detection, multiple images registration, target detection, coral reef and volcano monitoring. The objectives are achieved by accurate and early change detection in coral health, and volcanic activities, such as, by detecting color changes in crater lakes; accurate bottom-type classification in coral reefs; accurate concentration estimation of SO.sub.2, volcanic ashes, etc.; high temporal resolution of monitoring so that early mitigation steps can be activated; and high spatial resolution in multispectral and hyperspectral images. The same system can also be applied to other remote monitoring applications, such as, soil moisture monitoring.

Systems and methods are disclosed for identifying formerly conjoined pieces of tissue in a specimen, comprising receiving one or more digital images associated with a pathology specimen, identifying a plurality of pieces of tissue by applying an instance segmentation system to the one or more digital images, the instance segmentation system having been generated by processing a plurality of training images, determining, using the instance segmentation system, a prediction of whether any of the plurality of pieces of tissue were formerly conjoined, and outputting at least one instance segmentation to a digital storage device and/or display, the instance segmentation comprising an indication of whether any of the plurality of pieces of tissue were formerly conjoined.