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 an automated method of branch detection with regard to a blood vessel imaged using an intravascular modality such as OCT, IVUS, or other imaging modalities. In one embodiment, a representation of A-lines and frames generated using an intravascular imaging system is used to identify candidate branches of a blood vessel. One or more operators such as filters can be applied to remove false positives associated with other detections.
Abstract:
In part, the disclosure relates to systems and methods to assess stent/scaffold expansion in a vessel on an expedited time scale after stent/scaffold placement and expansion. In one embodiment, the method generates a first representation of a stented segment of the blood vessel indicative of a level of stent expansion; determines using the detected stent struts, a first end of the stent and a second end of the stent; and generate a second representation of the segment of the blood vessel by interpolating a lumen profile using an offset distance from the first end and the second end.
Abstract:
In part, the disclosure relates to intravascular data collection systems and the software-based visualization and display of intravascular data relating to detected side branches and detected stent struts. Levels of stent malapposition can be defined using a user interface such as a slider, toggle, button, field, or other interface to specify how indicia are displayed relative to detected stent struts. In addition, the disclosure relates to methods to automatically provide a two or three-dimensional visualization suitable for assessing side branch and/or guide wire location during stenting. The method can use one or more a computed side branch location, a branch takeoff angle, one or more stent strut locations, and one or more lumen contours.
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 method for identifying regions of interest in a blood vessel. The method includes the steps of: providing OCT image data of the blood vessel; applying a plurality of different edge detection filters to the OCT image data to generate a filter response for each edge detection filter; identifying in each edge detection filter response any response maxima; combining the response maxima for each edge detection filter response while maintaining the spatial relationship of the response maxima, to thereby create edge filtered OCT data; and analyzing the edge filtered OCT data to identify a region of interest, the region of interest defined as a local cluster of response maxima. In one embodiment, one or more indicia are positioned in one or more panels to emphasize a reference vessel profile as part of a user interface.
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 method for identifying regions of interest in a blood vessel. The method includes the steps of: providing OCT image data of the blood vessel; applying a plurality of different edge detection filters to the OCT image data to generate a filter response for each edge detection filter; identifying in each edge detection filter response any response maxima; combining the response maxima for each edge detection filter response while maintaining the spatial relationship of the response maxima, to thereby create edge filtered OCT data; and analyzing the edge filtered OCT data to identify a region of interest, the region of interest defined as a local cluster of response maxima. In one embodiment, one or more indicia are positioned in one or more panels to emphasize a reference vessel profile as part of a user interface.
Abstract:
In part, the disclosure relates to intravascular data collection systems and the software-based visualization and display of intravascular data relating to detected side branches and detected stent struts. Levels of stent malapposition can be defined using a user interface such as a slider, toggle, button, field, or other interface to specify how indicia are displayed relative to detected stent struts. In addition, the disclosure relates to methods to automatically provide a two or three-dimensional visualization suitable for assessing side branch and/or guide wire location during stenting. The method can use one or more a computed side branch location, a branch takeoff angle, one or more stent strut locations, and one or more lumen contours.
Abstract:
Aspects of the disclosure relate to the combination and display of both live and non-live patient images. The features described include collecting angiographic image data, and correlating angiographic image frames to time-varying data relating to the patient's heart cycle. This time-varying data may then be compared with the patient's live heart cycle data so that the collected angiographic image frames can be interlaced within a display of live fluoroscopic images of the patient.