Abstract: This system for training an operation determination model for a medical instrument control device generates training data by means of a reinforcement learning model, and, using the training data, can train an operation determination model configured to output information associated with operational commands for a driving unit that transports medical instruments.

Abstract: A method of classifying vessels, performed by at least one processor, the method including: acquiring an image including the cardiovascular vessels of a subject and angle information of an image acquisition device for the subject; and based on the angle information, identifying at least one type of cardiovascular vessel included in the image is disclosed.

Abstract: A blood vessel image segmentating method according to an embodiment may comprise the steps of: generating a plurality of candidate mask images regarding a target blood vessel by applying a plurality of blood vessel segmentation models on a blood vessel image; evaluating an error level for each of the generated plurality of candidate mask images; and generating a target blood vessel segmentation result from the candidate mask images, on the basis of the evaluated error level.

Abstract: An electronic device according to one embodiment can acquire a first trendline related to vessels from a medical image; determine lesion candidates among the vessels on the basis of the first trendline; acquire a second trendline on the basis of a reference point selected in the vicinity of the lesion candidates; and determine a lesion site among the lesion candidates on the basis of the acquired second trendline.

Abstract: An electronic device for processing a blood vessel image according to an embodiment may include: an arc-shaped C-arm open toward the isocenter; a radiation source connected to the C-arm and emitting radiation to a target blood vessel located on a table; and a processor for computing a target distance from the radiation source to the target blood vessel, on the basis of a first vertical distance from the isocenter to the table and a second vertical distance from the target blood vessel to the table, and computing a physical distance of the target blood vessel by using the computed target distance, from a blood vessel image obtained using radiation.

Abstract: Provided is a method for selecting an optimal frame using a distribution of intensities for each frame image of a medical image, which is performed by one or more processors of an information processing system. The method includes receiving a medical image associated with a blood vessel injected with a contrast agent, the medical image including a plurality of frame images, calculating an intensity for each of the plurality of frame images of the medical image, determining, based on a distribution of a plurality of intensities corresponding to the plurality of frame images, a frame section corresponding to a plurality of consecutive frame images of the plurality of frame images, and selecting, based on the determined frame section, a frame image from among the plurality of consecutive frame images.

Abstract: A method comprises receiving a user input to select a first point and a second point from a medical image, extracting a plurality of blood vessel regions from a plurality of frame images of the medical image, determining a plurality of first regions associated with the first point and a plurality of second regions associated with the second point, determining a first frame image and a second frame image with the contrast agent arriving at the first point and the second point, based on a change in pixel intensity for each of the plurality of first regions and the plurality of second regions, and computing the blood flow velocity from the first point to the second point based on a time interval between the first frame image and the second frame image and on a distance between the first point and the second point.

Abstract: Provided is a method for computing a SYNTAX score using a cardio angiogram, which is performed by at least one processor of a computing device, and includes acquiring an angiogram of a cardiovascular system, providing a cardiovascular segment map associated with the angiogram, in response to a user input that selects one of one or more frames included in the acquired angiogram and associates the selected one frame with a cardiovascular segment included in the cardiovascular segment map, associating the selected one frame with the cardiovascular segment, generating, using the selected one frame, an analysis result for a lesion in the associated cardiovascular segment, determining, based on the analysis result, a SYNTAX score for at least a part of the cardiovascular system, and generating an indication of the SYNTAX score.

Abstract: Provided is a method for generating an aneurysm region performed by an electronic device including: obtaining, by at least one processor, input images; generating, by the at least one processor, a vessel mesh based on the input images; determining, by the at least one processor, an adhered vessel from the vessel mesh; and separating, by the at least one processor, the adhered vessel based on user input.

Abstract: Provided is a method for determining a separating plane for separating aneurysm from a parent artery to obtain precise size information of an aneurysm. The method includes generating an aneurysm region including: generating a vessel mesh; generating a centerline based on the vessel mesh; generating a parent artery mesh based on the centerline; and generating a separating plane based on the parent artery mesh to obtain the aneurysm region.

Abstract: Provided is a method for generating an aneurysm region including: obtaining an input image; generating a vessel mesh based on the input image; generating a vessel network including a plurality of nodes based on the vessel mesh; and performing image processing on the vessel network to generate an aneurysm region.

Abstract: Provided is a method for determining a plane in three-dimensional shape to obtain precise size information of an aneurysm. The method includes generating an aneurysm region including: generating a vessel mesh; obtaining at least one input point; generating a separating plane based on the at least one input point; and generating the aneurysm region based on the separating plane.

Abstract: A method for processing a cardiovascular image for detection of cardiovascular lesions is provided, which is performed by one or more processors of a computing device. The method includes receiving a cardiovascular image, acquiring a first image mask corresponding to at least a part of blood vessels included in the cardiovascular image, acquiring a centerline image mask corresponding to centerlines of at least the part of blood vessels included in the cardiovascular image, extracting a first image patch from the cardiovascular image, extracting a second image patch from the centerline image mask, generating a refined third image patch by performing, based on the first image patch and the second image patch, a local refinement, and generating, based on the refined third image patch and the first image mask, a refined second image mask.

Abstract: A vascular image processing method performed by a processor includes extracting, from a vascular image, a first vascular region corresponding to an entire blood vessel included in the vascular image, a second vascular region corresponding to a target vessel and one or more branch vessels connected to the target vessel, and a third vascular region corresponding to the target vessel, and predicting a vascular structure in the vascular image, based on the first vascular region, the second vascular region, and the third vascular region, which are extracted from the vascular image.

Abstract: The present disclosure relates to a method, performed by a processor, for processing a blood vessel image from a blood vessel image, the method comprising the steps of: extracting a target blood vessel from a blood vessel image; determining a region of interest (ROI) in an extraction result of the target blood vessel on the basis of a first input received from a user; and within the determined ROI, identifying an error portion in the extraction result on the basis of a second input received from the user, and correcting the identified error portion.

Abstract: A method, performed by a processor, for processing a blood vessel image from an angiography image may comprise the steps of: extracting a target blood vessel from a blood vessel image; identifying an error portion from the extraction result of the target blood vessel on the basis of at least one of blood vessel structure data related to the target blood vessel, curvature information of the target blood vessel, diameter information of the target blood vessel, and brightness information of the target blood vessel; and in response to a case where an error portion is identified in the target blood vessel, correcting the identified error portion.

Abstract: This system for training an operation determination model for a medical instrument control device generates training data by means of a reinforcement learning model, and, using the training data, can train an operation determination model configured to output information associated with operational commands for a driving unit that transports medical instruments.

Abstract: A vascular image processing method performed by a processor includes extracting, from a vascular image, a first vascular region corresponding to an entire blood vessel included in the vascular image, a second vascular region corresponding to a target vessel and one or more branch vessels connected to the target vessel, and a third vascular region corresponding to the target vessel, and predicting a vascular structure in the vascular image, based on the first vascular region, the second vascular region, and the third vascular region, which are extracted from the vascular image.

Abstract: This system for training an operation determination model for a medical instrument control device generates training data by means of a reinforcement learning model, and, using the training data, can train an operation determination model configured to output information associated with operational commands for a driving unit that transports medical instruments.

Abstract: Provided is a method for selecting an optimal frame using a distribution of intensities for each frame image of a medical image, which is performed by one or more processors of an information processing system. The method includes receiving a medical image associated with a blood vessel injected with a contrast agent, the medical image including a plurality of frame images, calculating an intensity for each of the plurality of frame images of the medical image, determining, based on a distribution of a plurality of intensities corresponding to the plurality of frame images, a frame section corresponding to a plurality of consecutive frame images of the plurality of frame images, and selecting, based on the determined frame section, a frame image from among the plurality of consecutive frame images.