Abstract: The disclosure relates to systems and methods for real-time detection of a very large number of items in a given constrained volume. Specifically, the disclosure relates to systems and methods for retrieving an optimized set of classifiers from a self-updating classifiers' database, configured to selectively and specifically identify products inserted into a cart in real time, from a database comprising a large number of stock-keeping items, whereby the inserted items' captured images serve simultaneously as training dataset, validation dataset and test dataset for the recognition/identification/re-identification of the product.

Abstract: A three-dimensional geometric model of a heart can be generated from a plurality of two-dimensional image slices of the heart collected using an intracardiac echocardiography (“ICE”) catheter. Each image slice can be associated with localization information for the ICE catheter. The image slices can be output in a plurality of voxels according to their associated localization information, thereby creating a three-dimensional geometric model of the heart. Data sufficiency of the three-dimensional model can also be graphically represented. For example, data sufficiency can be represented using voxel opacity, a one-dimensional illustration, a two-dimensional illustration, and/or a data collection cue.

Abstract: Al-based computer vision algorithms, operating in the real world rather than in the digital domain, typically operate in a certain three-dimensional space. The system, programs and method provided herein, describe a system that allows limiting the execution of Al algorithms to operate only on objects breaching a predefined and confined plane (also termed grid) or a volume in space. In other words, the system programs and method provided herein define a 2D/2.5D/3D regions or grid in space, operable to detect any change which occurs in and through this grid. This ability includes in certain implementations, the detection of any animate or inanimate object, or multiple grouped objects which may cross, pass or introduced to this grid, their type, identification and action assigning.

Abstract: The disclosure relates generally to the field of vascular system and peripheral vascular system data collection, imaging, image processing and feature detection relating thereto. In part, the disclosure more specifically relates to methods for detecting position and size of contrast cloud in an x-ray image including with respect to a sequence of x-ray images during intravascular imaging. Methods of detecting and extracting metallic wires from x-ray images are also described herein such as guidewires used in coronary procedures. Further, methods for of registering vascular trees for one or more images, such as in sequences of x-ray images, are disclosed. In part, the disclosure relates to processing, tracking and registering angiography images and elements in such images. The registration can be performed relative to images from an intravascular imaging modality such as, for example, optical coherence tomography (OCT) or intravascular ultrasound (IVUS).

Abstract: The disclosure relates generally to the field of vascular system and peripheral vascular system data collection, imaging, image processing and feature detection relating thereto. In part, the disclosure more specifically relates to methods for detecting position and size of contrast cloud in an x-ray image including with respect to a sequence of x-ray images during intravascular imaging. Methods of detecting and extracting metallic wires from x-ray images are also described herein such as guidewires used in coronary procedures. Further, methods for of registering vascular trees for one or more images, such as in sequences of x-ray images, are disclosed. In part, the disclosure relates to processing, tracking and registering angiography images and elements in such images. The registration can be performed relative to images from an intravascular imaging modality such as, for example, optical coherence tomography (OCT) or intravascular ultrasound (IVUS).

Abstract: A registration fixture or plate is configured for use with a medical imaging system. The registration fixture may be an optical magnetic registration plate including a plurality of fiducial markers in arranged in a predefined unique pattern. The pattern can be unambiguously detected on 2D image of the plate produced by the medical imaging system. Association of the 2D imaged pattern of fiducial markers with the actual 3D pattern on the optical magnetic registration plate allows for accurate calculation of projection matrices and co-registration of the 3D and 2D coordinate systems.

Abstract: The disclosure relates to systems and methods for real-time detection of a very large number of items in a given constrained volume. Specifically, the disclosure relates to systems and methods for retrieving an optimized set of classifiers from a self-updating classifiers' database, configured to selectively and specifically identify products inserted into a cart in real time, from a database comprising a large number of stock-keeping items, whereby the inserted items' captured images serve simultaneously as training dataset, validation dataset and test dataset for the recognition/identification/re-identification of the product.

Abstract: The disclosure is directed to system, methods and programs for automatic verification and validation of users' actions during assembly of products intended for purchase in a shopping cart, more specifically, the disclosure is directed to systems, methods and programs for automatically validating correct identification and markings of items inserted to an artificially intelligent shopping cart by using action-recognition associated with correct scanning/presentation of the item to a product recognition module coupled to the artificially intelligent shopping cart.

Abstract: The disclosure relates to systems and methods for real-time detection of a very large number of items in a given constrained volume. Specifically, the disclosure relates to systems and methods for retrieving an optimized set of classifiers from a self-updating classifiers' database, configured to selectively and specifically identify products inserted into a cart in real time, from a database comprising a large number of stock-keeping items, whereby the inserted items' captured images serve simultaneously as training dataset, validation dataset and test dataset for the recognition/identification/re-identification of the product.

Abstract: The disclosure relates to systems and methods for automatic detection of product insertion and product extraction in an Artificial Intelligent Cart (AIC). Specifically, the disclosure relates to systems and methods of ascertaining insertion and extraction of product into and from an open shopping cart, by continuously monitoring triggered content changes.

Abstract: The disclosure relates to systems and methods for automatic detection of product insertion and product extraction in an Artificial Intelligent Cart (AIC). Specifically, the disclosure relates to systems and methods of ascertaining insertion and extraction of product into and from an open shopping cart, by continuously monitoring triggered content changes.

Abstract: The disclosure relates to systems and methods for real-time detection of a very large number of items in a given constrained volume. Specifically, the disclosure relates to systems and methods for retrieving an optimized set of classifiers from a self-updating classifiers' database, configured to selectively and specifically identify products inserted into a cart in real time, from a database comprising a large number of stock-keeping items, whereby the inserted items' captured images serve simultaneously as training dataset, validation dataset and test dataset for the recognition/identification/re-identification of the product.

Abstract: The disclosure relates to systems and methods for real-time detection of a very large number of items in a given constrained volume. Specifically, the disclosure relates to systems and methods for retrieving an optimized set of classifiers from a self-updating classifiers' database, configured to selectively and specifically identify products inserted into a cart in real time, from a database comprising a large number of stock-keeping items, whereby the inserted items' captured images serve simultaneously as training dataset, validation dataset and test dataset for the recognition/identification/re-identification of the product.

Abstract: The disclosure relates generally to the field of vascular system and peripheral vascular system data collection, imaging, image processing and feature detection relating thereto. In part, the disclosure more specifically relates to methods for detecting position and size of contrast cloud in an x-ray image including with respect to a sequence of x-ray images during intravascular imaging. Methods of detecting and extracting metallic wires from x-ray images are also described herein such as guidewires used in coronary procedures. Further, methods for of registering vascular trees for one or more images, such as in sequences of x-ray images, are disclosed. In part, the disclosure relates to processing, tracking and registering angiography images and elements in such images. The registration can be performed relative to images from an intravascular imaging modality such as, for example, optical coherence tomography (OCT) or intravascular ultrasound (IVUS).

Abstract: A three-dimensional geometric model of a heart can be generated from a plurality of two-dimensional image slices of the heart collected using an intracardiac echocardiography (“ICE”) catheter. Each image slice can be associated with localization information for the ICE catheter. The image slices can be output in a plurality of voxels according to their associated localization information, thereby creating a three-dimensional geometric model of the heart. Data sufficiency of the three-dimensional model can also be graphically represented. For example, data sufficiency can be represented using voxel opacity, a one-dimensional illustration, a two-dimensional illustration, and/or a data collection cue.

Abstract: The disclosure relates generally to the field of vascular system and peripheral vascular system data collection, imaging, image processing and feature detection relating thereto. In part, the disclosure more specifically relates to methods for detecting position and size of contrast cloud in an x-ray image including with respect to a sequence of x-ray images during intravascular imaging. Methods of detecting and extracting metallic wires from x-ray images are also described herein such as guidewires used in coronary procedures. Further, methods for of registering vascular trees for one or more images, such as in sequences of x-ray images, are disclosed. In part, the disclosure relates to processing, tracking and registering angiography images and elements in such images. The registration can be performed relative to images from an intravascular imaging modality such as, for example, optical coherence tomography (OCT) or intravascular ultrasound (IVUS).

Abstract: The instant disclosure relates to systems and methods for identifying fiducial markers on one or more images of an anatomical region of a patient. Prior to the identification of the fiducial markers, other objects are identified and removed. In particular, some embodiments are directed toward the detection of fiducial markers in the presence of catheters and other medical devices in a fluoroscopic image. In such an embodiment, identifying and removing the medical devices from the clinical image aids in properly identifying the fiducial markers.

Abstract: In part, the invention relates to processing, tracking and registering angiography images and elements in such images relative to images from an intravascular imaging modality such as, for example, optical coherence tomography (OCT). Registration between such imaging modalities is facilitated by tracking of a marker of the intravascular imaging probe performed on the angiography images obtained during a pullback. Further, detecting and tracking vessel centerlines is used to perform a continuous registration between OCT and angiography images in one embodiment.

Abstract: A registration fixture or plate is configured for use with a medical imaging system. The registration fixture may be an optical magnetic registration plate including a plurality of fiducial markers in arranged in a predefined unique pattern. The pattern can be unambiguously detected on 2D image of the plate produced by the medical imaging system. Association of the 2D imaged pattern of fiducial markers with the actual 3D pattern on the optical magnetic registration plate allows for accurate calculation of projection matrices and co-registration of the 3D and 2D coordinate systems.

Abstract: The disclosure relates generally to the field of vascular system and peripheral vascular system data collection, imaging, image processing and feature detection relating thereto. In part, the disclosure more specifically relates to methods for detecting position and size of contrast cloud in an x-ray image including with respect to a sequence of x-ray images during intravascular imaging. Methods of detecting and extracting metallic wires from x-ray images are also described herein such as guidewires used in coronary procedures. Further, methods for of registering vascular trees for one or more images, such as in sequences of x-ray images, are disclosed. In part, the disclosure relates to processing, tracking and registering angiography images and elements in such images. The registration can be performed relative to images from an intravascular imaging modality such as, for example, optical coherence tomography (OCT) or intravascular ultrasound (IVUS).