Abstract: The present disclosure relates to an object selection system that accurately detects and automatically selects target instances of user-requested objects (e.g., a query object instance) in a digital image. In one or more embodiments, the object selection system can analyze one or more user inputs to determine an optimal object attribute detection model from multiple specialized and generalized object attribute models. Additionally, the object selection system can utilize the selected object attribute model to detect and select one or more target instances of a query object in an image, where the image includes multiple instances of the query object.

Abstract: Systems and methods are disclosed for assessing cardiovascular disease and treatment effectiveness based on adipose tissue. One method includes identifying a vascular bed of interest in a patient's vasculature; receiving a medical image of the patient's identified vascular bed of interest; identifying adipose tissue in the received medical image; receiving a geometric vascular model comprising a representation of the patient's identified vascular bed of interest; and computing an inflammation index associated with the geometric vascular model, using the identified adipose tissue.

Abstract: A medical scan viewing system is conFIG.d to: receive a first medical scan and a second medical scan from a medical picture archive system, the first medical scan associated with a unique patient ID and a first scan date and the second medical scan associated with the unique patient ID and a second scan date; identify locations of anatomical landmarks in the first medical scan; identifying corresponding locations of the anatomical landmarks in the second medical scan; co-register the first medical scan with the second medical scan based on the locations of the anatomical landmarks in the first medical scan with the corresponding locations of the anatomical landmarks in the second medical scan; and present for display, via an interactive user interface, the first medical scan with the second medical scan, wherein the first medical scan and the second medical scan are synchronously presented, based on the co-registering.

Abstract: The present disclosure relates to a system (100) for scoring motion of a heart wall (214, 218). The system (100) includes an imaging system (102) operable to acquire a first image (230) of the heart wall (214, 218) at a first time and a second image (240) of the heart wall (214, 218) at a second time. A processor (108) is provided to identify a first set of contour data in the first image (230); and a second set of contour data in the second image (240). The processor (108) defines at least one element (Ei) representing a cardiac cyclic change in a section of the heart wall (214, 218) in dependence on the first and second sets of contour data. Each element (Ei) is analysed to generate at least one metric which is compared with a reference data model to score the motion of the corresponding section of the heart wall (214, 218). The disclosure also relates to a method of scoring motion of a heart wall (214, 218); and a non-transitory computer-readable medium.

Abstract: An object of the present disclosure is to create an album having both the contents common to all persons and the contents in accordance with each individual. One embodiment of the present disclosure is an apparatus that creates albums for each main object, which consist of a plurality of double-page spreads including a common double-page spread used in common in at least two albums and an individual double-page spread corresponding to the main object.

Abstract: Method and systems for identifying dangers in an accessible environment. Computer vision and video analysis is performed on one or more images and/or video of the accessible environment to generate a series of still frames for a database of training images and natural language processing (NLP) is performed on one or more written reports to generate textual parameters. An online image similarity search is performed using the textual parameters to generate additional images for the database of training images and a risk/danger prediction model is generated based on the database of training images. One or more potential dangers are identified, and one or more warnings are generated using the risk/danger prediction model.

Abstract: A nasal-cavity model generator (41) extracts pixels having pixel density values within a specific range from three-dimensional image data on a nasal cavity of a subject contained in DICOM data (21), and generates a nasal cavity model (50), which is a three-dimensional model of the nasal cavity, based on three-dimensional image data composed of the extracted pixels. A nasal-cavity resistance calculator (42) calculates a nasal cavity resistance (51) through fluid analysis using the nasal cavity model (50) generated by the nasal-cavity model generator (41). An adjuster (43) adjusts the specific range of the pixel density values of the pixels to be extracted for generation of the nasal cavity model (50) by the nasal-cavity model generator (41) such that the nasal cavity resistance (51) calculated by the nasal-cavity resistance calculator (42) is equal to a nasal cavity resistance (52) actually measured with a nasal-cavity draft gauge.

Abstract: The present disclosure provides systems and methods to receiving OCT or IVUS image data frames to output one or more representations of a blood vessel segment. The image data frames may be stretched and/or aligned using various windows or bins or alignment features. Arterial features, such as the calcium burden, may be detected in each of the image data frames. The arterial features may be scored. The score may be a stent under-expansion risk. The representation may include an indication of the arterial features and their respective score. The indication may be a color coded indication.

Abstract: The application provides a method, system for registration of a bone, and a trackable element, it is configured to obtain a mark point information which can be obtained from a certain operation performed by a distal end of a trackable element on a surface of the bone when a switch of the trackable element meets a setting condition corresponding to the operation; and to perform a virtual reconstruction of the surface of the bone according to the obtained mark point information and an image data of the bone which is obtained in advance. As a result, a precise registration of the patient's physical space coordinate system and image space coordinate system can be achieved, during which only one operator is enough for completing the registration. Therefore, operations with high accuracy and convenience are ensured, which can significantly improve the registration efficiency, and the operating experience of operators.

Abstract: A stress prediction device for predicting mechanical stress exerted to a deformable object due contact between the object and an external device that is to be inserted into the object at an intended insertion position comprises a segmentation unit configured to access generic model data representing a generic reference object that comprises predefined secondary landmark features at predefined landmark positions, which are not identifiable using a predefined imaging technique, and pre-insertion object image data acquired using the imaging technique. It provides segmented object model data which comprises associated mapped landmark position data indicative of mapped landmark positions of the secondary landmark features. A stress determination unit determines and provides predictive stress information indicative of mechanical stress exerted to at least one of the secondary landmark features at the associated mapped landmark position due to mechanical contact between the object and the external device.

Abstract: In various embodiments, the present invention provides an improved system and method for motion estimation and motion compensation in cone beam computer tomography (CBCT). The present invention utilizes a method for alternating minimization between volume and motion sub-iterations and results in an improved system and method for motion estimation and compensation in CBCT.

Abstract: A classification unit classifies messages included in a text log depending on types, and gives an ID set for each type to each of the classified messages. A creation unit creates, based on dates of occurrence attached to the messages, a matrix indicating an appearance distribution of the messages in the text log for each predetermined duration for each ID. A pattern extraction unit extracts a plurality of patterns, which are combinations of the IDs, from the matrix created by the creation unit. A removal unit removes a part or whole of the patterns from the matrix. A determination unit calculates a degree of importance for each element included in each of the patterns, and determines whether the degree of importance is equal to or higher than a predetermined threshold. A sequence extraction unit extracts a sequence.

Abstract: Techniques for generating a digital collage using digital images are described. An image editing system obtains a set of digital images and a collage template to be used for generating a digital collage. The image editing system calculates different arrangement permutations for placing the digital images into digital frames of the collage template, and identifies a region of interest in each of the digital images. The image editing system fits the digital images into the digital frames for each of the arrangement permutations, and calculates a permutation error value for each arrangement permutation based on proportions of the regions of interest for each of the digital images that fit into respective digital frames. The image editing system selects an arrangement permutation with an optimal permutation error value, and uses the selected arrangement permutation to arrange the set of digital images in the collage template to generate the digital collage.

Abstract: A non-transitory computer-readable medium stores instructions readable and executable by a workstation (14) operatively connected to a display device (20) and including at least one electronic processor (16) to perform an image acquisition and reconstruction method (101). The method includes: retrieving a non-voxel-based reconstructed image comprising non-voxel image elements from a picture and archiving communication system (PACS) database (24) to the workstation; at the workstation, generating at least one voxel-based resampled image from the non-voxel-based reconstructed image; and displaying the at least one voxel-based reconstructed image on the display device.

Abstract: A method and system for fast non-invasive computer-based computation of a hemodynamic index, such as fractional flow reserve (FFR) from medical image data of a patient is disclosed. A patient-specific anatomical model of one or more arteries of a patient is automatically generated based on medical image data of the patient. Regions in the automatically generated patient-specific anatomical model for which user feedback is required for accurate computation of a hemodynamic index are predicted using one or more trained machine learning models.

Abstract: Described herein are systems, methods and instrumentalities associated with motion tracking and strain determination. A motion tracking apparatus as described herein may track the motion of an anatomical structure from a source image to a target image and determine corresponding points on one or more surfaces of the anatomical structure in both the source image and the target image. Using these surface points, the motion tracking apparatus may calculate one or more strain parameters associated with the anatomical structure and provide the strain parameters for medical diagnosis and/or treatment.

Abstract: The described technology is generally directed towards comparing two images for content differences, such as images based on the frames of a show and a derivative version of that show. Frame pairs such as from an original show and its derivative version are processed into image pairs, which can include decoding, scaling, luminance extraction and/or filtering. An edge pixel image is obtained via edge detection for each image. Edge pixels in one image are compared against a counterpart edge pixel (and possibly neighboring pixels) in the other image to determine matches (matching edge pixels) and mismatches. An image with too many errors based on the mismatches is deemed as a candidate for further review. A difference image can be generated to assist a reviewer in detecting where the mismatches were detected. By repeating for the various frames, a show can be automatically compared against its derivative for content differences.

Abstract: An image with a known, first classification by the machine learning model is received. This image is then iteratively modified using at least one perturbation algorithm and such modified images are input into the machine learning model until such time as the machine learning model outputs a second classification different from the first classification. Data characterizing the modifications to the image that resulted in the second classification can be provided (e.g., displayed in a GUI, loaded into memory, stored in physical persistence, transmitted to a remote computing device). Related apparatus, systems, techniques and articles are also described.

Abstract: According to one embodiment, a medical image processing apparatus includes first specifier, second specifier, determiner and display controller. First specifier collates an ischemic region calculated from a blood vessel visualized into a three-dimensional image in a plurality of phases with a dominating region of the blood vessel, and specifies a culprit vessel in the ischemic region. Second specifier specifies a culprit stenosis in the culprit vessel based on a pressure index calculated from the blood vessel. Determiner determines a connection position to connect a bypass vessel that makes a detour around the culprit stenosis. Display controller displays the determined connection position on a display.

Abstract: A computer-implemented tool for automated classification and interpretation of documents, such as life science documents supporting clinical trials, is configured to perform a combination of raw text, document construct, and image analyses to enhance classification accuracy by enabling a more comprehensive machine-based understanding of document content. The combination of analyses provides context for classification by leveraging relative spatial relationships among text and image elements, identifying characteristics and formatting of elements, and extracting additional metadata from the documents as compared to conventional automated classification tools.