LightLab Imaging, Inc.

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 side branch obstruction. An estimate of side branch diameter can be made based on a vessel profile or a maximum diameter of a vessel at a distal and proximal location relative to the side branch. A amount of side branch obstruction may be determined by comparing an observed side branch diameter with in the image data with the estimated side branch diameter. In addition, an amount of blood flow obstruction may also be determined.

Aspects of the disclosure provide for automated self-inspection by an OCT imaging engine or device, to identify and resolve failures or inefficiencies in the hardware and/or software of the system or device during imaging. An OCT imaging engine can include a catheter connection check system for checking the quality of a physical connection point between a catheter and other components of an OCT imaging device or system. In some examples, the OCT imaging engine includes a self-inspection engine implemented to perform routine self-inspection by using a reference reflector internal to the OCT imaging engine to generate system performance data. The OCT imaging engine can use the system performance data to periodically search for and resolve failures or inefficiencies in the system. The OCT imaging engine can perform a self-calibration process to perform k-linearization and/or correct for chromatic dispersion using mirror measurements collected from an internal reference reflector.

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.

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.

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).

In part, the invention relates to a probe suitable for use with image data collection system. The probe, in one embodiment, includes an optical transceiver, such as a beam director, and an acoustic transceiver such as an ultrasound transducer. The optical transceiver is in optical communication with an optical fiber in optical communication with a beam director configured to transmit light and receive scattered light from a sample such as a wall of a blood vessel. The acoustic transceiver includes an ultrasound device or subsystem such as a piezoelectric element configured to generate acoustic waves and receive reflected acoustic waves from the sample.

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.

Aspects of the disclosure provide for an x-ray detection device for detecting radiation scattered off of a target during an imaging procedure and generating temporal data indicating the time of occurrence of a pulse of radiation emitted towards the target. The temporal data can be sent to a host device and used to timestamp images generated from the pulses of radiation. The x-ray detection device is portable and can be installed in a catheterization laboratory or imaging environment to detect the occurrence of radiation, without occluding or partially occluding the beam source. Aspects of the disclosure also provide for a system for receiving temporal data generated by the x-ray detection device, and accurately tagging received image frames based on the temporal data.

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).

A method and apparatus of automatically locating in an image of a blood vessel the lumen boundary at a position in the vessel and from that measuring the diameter of the vessel. From the diameter of the vessel and estimated blood flow rate, a number of clinically significant physiological parameters are then determined and various user displays of interest generated. One use of these images and parameters is to aid the clinician in the placement of a stent. The system, in one embodiment, uses these measurements to allow the clinician to simulate the placement of a stent and to determine the effect of the placement. In addition, from these patient parameters various patient treatments are then performed.