A method, apparatus, device, and storage medium for transforming a hairstyle are provided. The method may include: determining a face bounding box according to information on face key points of acquired face image; constructing grids according to the face bounding box; deforming, by using an acquired target hairstyle function, edge lines of at least a part of the constructed grids, which comprises the hairstyle, to obtain a deformed grid curve; determining a deformed hairstyle in the face image according to the deformed grid curve.

Methods, systems, and articles of manufacture, including computer program products, are provided for image cleanup. In some embodiments, there is provide a method which may include subsampling a first image to a first level image of a multiscale transform; performing, based on a machine learning model, an identification of a foreground portion of the first level image and a background portion of the first level image; generating, based on the identification of the foreground portion and the background portion, a first mask; upscaling the first mask to a resolution corresponding to the first image depicting the foreground item; applying the upscaled first mask to the first image to form a second image depicting the foreground item; and providing the second image depicting the foreground item to a publication system. Related systems and articles of manufacture, including computer program products, are also provided.

A damage evaluation device, a method, and a program that can automatically evaluate a damage of an outer layer of a structure occurring with respect to construction of the structure are provided. In a damage evaluation device of a structure including a processor, the processor is configured to perform image acquisition processing of acquiring a captured image of the structure, perform damage detection processing of detecting damages (cracks) of the structure based on the acquired image, perform feature region detection processing of detecting a structure feature region (a region of a P cone mark) related to construction of the structure based on the acquired image, perform selection processing of selecting a specific damage (settlement crack) related to the detected structure feature region among the detected damages, and perform information output processing of outputting information about the selected specific damage. By outputting the information about the specific damage, the damage of the outer layer of the structure occurring with respect to the construction of the structure can be automatically evaluated, and application to validity verification of a construction method and improvement of the construction method can be made.

Systems and methods of fluid or air passageway cross-sectional area determination in an anatomy are disclosed. In some examples, the methods may include generating a model of a structure based on a plurality of images of the structure, the structure comprising at least one fluid or air flow path. In some examples, the methods may also include identifying an obstruction element in the model of the structure, the obstruction element affecting the at least one fluid or air flow path in the model. In some examples, the methods may also include determining a region of the at least one fluid or air flow path for flow analysis.

Methods, systems, and articles of manufacture, including computer program products, are provided for image cleanup. In some embodiments, there is provide a method which may include subsampling a first image to a first level image of a multiscale transform; performing, based on a machine learning model, an identification of a foreground portion of the first level image and a background portion of the first level image; generating, based on the identification of the foreground portion and the background portion, a first mask; upscaling the first mask to a resolution corresponding to the first image depicting the foreground item; applying the upscaled first mask to the first image to form a second image depicting the foreground item; and providing the second image depicting the foreground item to a publication system. Related systems and articles of manufacture, including computer program products, are also provided.

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.

A system and method for automatically analyzing placenta insufficiency in a curved topographical ultrasound image slice is provided. The method includes acquiring, by an ultrasound system, an ultrasound volume of a placental anatomy section, the ultrasound volume comprising color Doppler information. The method includes extracting, by at least one processor of the ultrasound system, a topographical ultrasound image slice at a distance below an inner surface of the placental anatomy section. The topographical ultrasound image slice is curved in all three dimensions and includes the color Doppler information. The method includes analyzing, by the at least one processor, the color Doppler information of the topographical ultrasound image slice to generate perfusion data information. The method includes causing, by the at least one processor, a display system to present the topographical ultrasound image slice with the perfusion data information.

The present invention is related to improved methods for analysis of images of the vitreous and/or retina and/or choroid obtained by optical coherence tomography and to methods for making diagnoses of retinal disease based on the reflectivity profiles of various vitreous and/or retinal and/or choroidal layers of the retina.

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.

A time series of image frames in an anatomical scan is segmented. An image frame k in the time series of image frames is manually segmented. A non-rigid registration is then performed between the image frame k and a next image frame k+1 in the time series of image frames. A segmentation on the image frame k+1 is computed based on the non-rigid registration. Each subsequent image frame k+n in the time series of image frames is iteratively segmented using non-rigid registration with the segmented previous image frame k+(n−1) in the time series of image frames.