Abstract: A method includes receiving an image from a mammogram, removing noise from the image, computing a point of interest on the de-noised image, creating a mesoscale region of interest on the de-noised image, computing a connectivity for the mesoscale region of interest, identifying a connected component using the computed connectivity, where the connected component represents a branch of a global curvilinear structure, selecting a set of branches based on a physical property for each branch of the global curvilinear structure, pruning each branch based on an error-tolerant, adaptive polynomial fit, identifying remaining regions of interest in each pruned branch, and growing a chain formed by remaining points of interest included in the remaining regions of interest, where the chain represents a macroscopic, global curvilinear calcified arterial structure. The quantitation of the calcified arterial structures may be used as a biomarker for risk stratification of heart disease.

Abstract: A method for operating a laser distance measuring device, in particular a hand-held laser distance measuring device, includes determining a first distance from a first target point with a laser distance measuring unit of the laser distance measuring device by emitting a laser beam in a first distance measuring direction. The method further includes subsequently determining at least one second distance from a second intended target point. An image at least of the target environment of the second target point, captured by a camera of the laser distance measuring device, is displayed on a display of the laser distance measuring device. At least one part of a connection line is represented overlapping with the image, and the connection line connects the first target point and the second target point in the displayed image. A laser distance measuring device implements the method in one embodiment.

Abstract: A neural network model fusion method and an electronic device using the same are provided. The neural network model fusion method includes the following steps. An image is received. The image is analyzed through several neural network models. The neural network models include at least two of a degree classification model, a multi-class identification model and an object detection model. Several analysis results are obtained according to the neural network models. These analysis results are converted into a number of conversion factors. The conversion factors are inputted into a fusion model to obtain a fusion result.

Abstract: Optimizations are provided for segmenting tissue objects included in an ultrasound image. Initially, raw pixel data is received. Here, each pixel corresponds to ultrasound information. This raw pixel data is processed through a first fully convolutional network to generate a first segmentation label map. This first map includes a first set of objects that have been segmented into a coarse segmentation class. Then, this first map is processed through a second fully convolutional network to generate a second segmentation label map. This second map is processed using the raw pixel data as a base reference. Further, this second map includes a second set of objects that have been segmented into a fine segmentation class. Then, a contour optimization algorithm is applied to at least one of the second set of objects in order to refine that object's contour boundary. Subsequently, that object is identified as corresponding to a lymph node.

Abstract: There is provided a method of computing a likelihood of malignancy in a mammographic image, comprising: receiving a single channel 2D mammographic image including a single pixel intensity value for each pixel thereof, converting the single channel 2D mammographic image into a multi channel 2D mammographic image including multiple pixel intensity value channels for each pixel thereof, computing by a first sub-classifier according to the whole multi channel image, a first score indicative of likelihood of malignancy within the whole multi channel image, computing by a second sub-classifier according to each respective patch extracted from the multi channel image, a respective second score indicative of likelihood of malignancy within each respective patch, and computing by a gating sub-classifier according to the first score and the second scores, an indication of likelihood of malignancy and a location of the malignancy.

Abstract: A hardware system is configured for, and a method of, generating detail-rich gradient-based disparity maps in real-time using an automated gradient-based disparity map classification process that is scalable, can be used under different environment conditions with little to no restrictions, and whose level of precision can be adjusted in a scalable manner. Highly accurate cross-spectral stereo matching methods may be used for search and rescue operations and work at day time and night time using current and past visual and full infrared imaging to generate, classify, and identify scenes in real-time with minimum constraints. Such system and methods may be used to improve operations of existing search and rescue equipment.

Abstract: A method and system to correct for alignment errors between assumed and actual geometric parameters of an acquisition geometry during image reconstruction in a chest tomosynthesis application includes receiving at least 2 raw projection images acquired on at least 2 different positions in a known acquisition geometry, determining an actual geometric parameter value by determining the minimum of a redundant planes cost function which is calculated for a varying range of the geometric parameter values, and which is determined by: a) at least one plane which intersects an X-ray source trajectory with at least two points, b) an intersection between the planes and a detector surface for which points the source positions are determined, and c) for which the parameters determining the intersection (?, ?, l) are used for the construction of the cost function, applying the calculated actual geometric parameter value of the acquisition geometry for the image reconstruction of the plurality of images, characterized in t

Abstract: The present invention provides a medical image processing method and a computer-readable storage medium. The method includes: reconstructing a two-dimensional cross-sectional image of an imaged tissue based on a volumetric image of the imaged tissue; projecting a CT value of the imaged tissue along a normal direction of the centerline of the imaged tissue in the two-dimensional cross-sectional image; and, positioning the imaged tissue based on the projection result of the CT value of the imaged tissue.

Abstract: An image processing apparatus is configured to extract an object region from an image. The image processing apparatus includes: a setting unit configured to set a plurality of reference points in the image; an obtaining unit configured to obtain a contour of the object region corresponding to each of the plurality of reference points as an initial extraction result based on a characteristic of the object region; and an extraction unit configured to extract the object region from the image based on an integration result obtained by integrating values of pixels in a plurality of initial extraction results.

Abstract: An automatic classification method for distinguishing between indolent and clinically significant carcinoma using multiparametric MRI (mp-MRI) imaging is provided. By utilizing a convolutional neural network (CNN), which automatically extracts deep features, the hierarchical classification framework avoids deficiencies in current schemes in the art such as the need to provide handcrafted features predefined by a domain expert and the precise delineation of lesion boundaries by a human or computerized algorithm. This hierarchical classification framework is trained using previously acquired mp-MRI data with known cancer classification characteristics and the framework is applied to mp-MRI images of new patients to provide identification and computerized cancer classification results of a suspicious lesion.

Abstract: Disclosed herein are a display apparatus which facilitates a simultaneous comparison of a plurality of images which respectively illustrate different features on one divided display screen such that the images are seamlessly displayed on the screen, and an image display method which is performable by using the apparatus. The display apparatus includes a memory configured to store a plurality of different types of images of an object, an input device configured to receive an input of a command relating to simultaneously displaying the different types of images, and a display device configured to display images. Upon receiving the command, the display device divides a screen upon which an image of the object is displayable into a first region within which a first image showing one portion of the object is displayed and a second region within which a second image showing the remaining portion of the object is displayed.

Abstract: A correction image fluctuation amount obtained in a calibration mode and a measurement image fluctuation amount obtained in a measurement mode are compared with each other. On the basis of the comparison result, a temporary correction value, which satisfies a specific condition among temporary correction values stored in the correction value storage unit, is determined as a measurement correction value to be used for correction in a correcting unit.

Abstract: A computer visual guidance system for guiding a surgeon through an arthroscopic debridement of a bony pathology, wherein the computer visual guidance system is configured to: (i) receive a 2D image of the bony pathology from a source; (ii) automatically analyze the 2D image so as to determine at least one measurement with respect to the bony pathology; (iii) automatically annotate the 2D image with at least one annotation relating to the at least one measurement determined with respect to the bony pathology so as to create an annotated 2D image; and (iv) display the annotated 2D image to the surgeon so as to guide the surgeon through the arthroscopic debridement of the bony pathology.

Abstract: Methods and systems for detecting orientation parameters of spherical objects by image processing are utilized to generate geometric models of the objects and displaying overlay graphics of the models in combination with original images which contain the objects. This process is utilized for detecting the orientation parameters of an artificial hip joint from an x-ray image and generating a geometric model of portions of the joint to be displayed as overlay graphics in combination with the original x-ray image. A disclosed embodiment detects the rotation of a basketball from video frame images and generates geometric models of the basketball including surface markings and rotational parameters which may be displayed as overlay graphics in combination with the original video image frames.

Abstract: A method of interactive quantification of digitized 3D objects includes a determination of coordinates of observed screen space using a camera that senses the position of pupils of the operator gazing on the screen. Dimensions of studied sub-volume of VOI block of dimensions of Sx, Sy, Sz or VOI cylinder of dimensions of Sx=Sy=Sxy are defined. An analyzed particle and VOI position is selected. A VOI is visualized. Observed space is corrected by VOI visualization. The last level is selected by gaze of the operator from the sequence of probe levels and the gaze is focused on the last level on which the particle is still visible. The property of the marked particle in 3D space is verified, and marked with a color mark. The mark position is determined by interpolation or by finding a representative point.

Abstract: Systems and methods here may include utilizing a computer with a processor and a memory for receiving a pixelated image of an original size, converting the pixelated image to grayscale, calculating a magnitude of spatial gradients in the received pixelated grayscale image, downscaling the received pixelated grayscale image, computing a multiplicative gain correction for the downscaled received pixelated grayscale image, re-enlarging a gain multiplication for the original image, and applying the gain multiplication to the image to generate a processed image with higher contrast than the received pixelated image.

Abstract: A triage routing system is operable to receive a medical scan via a receiver. Inference data for the medical scan is generated by performing an inference function, where the inference function utilizes a computer-vision model trained on a plurality of medical scans. One of a plurality of medical professionals is selected to review the medical scan based on the inference data. Triage routing data that indicates the medical scan and the one of the plurality of medical professionals is generated. The medical scan is transmitted to a client device associated with the one of the plurality of medical professionals for display via a display device in accordance with the triage routing data.

Abstract: The present invention relates to an apparatus (10) for feature suppression in dark field or phase contrast X-ray imaging. The apparatus comprises an input unit (20), a processing unit (30) and an output unit (40). The input unit is configured to provide the processing unit with an X-ray attenuation image of a region of interest of an object. The input unit is also configured to provide the processing unit with a dark field or phase contrast X-ray image of the region of interest of the object. The processing unit is further configured to identify a first feature in the X-ray attenuation image; to identify a second anatomical feature in the X-ray attenuation image; and to identify the second anatomical feature in the dark field or phase contrast X-ray image. The first feature is an obscuring anatomical feature depicted in the X-ray attenuation image with higher contrast than in the dark field or phase contrast X-ray image.

Abstract: A first analysis unit (202) acquires second image data. The second image data is generated by compressing first image data by a predetermined encoding method. Further, the first analysis unit (202) performs image analysis of the acquired second image data to detect second image data satisfying a first predetermined condition. A decoding unit (204) decodes second image data detected by the first analysis unit (202) into third image data having higher resolution than that of the second image data. In the second analysis (206), the image analysis of the third image data is performed.

Abstract: An image processing device and an image processing method are disclosed. The image processing method comprises: acquiring an image; segmenting the acquired image by using a deep learning-based segmentation process to obtain a binarized image labeled with a region of interest; processing a pixel matrix of the acquired image by using a pixel matrix of the binarized image to obtain a segmented image; and performing super-resolution reconstruction on the segmented image by using a deep learning-based super-resolution neural network to obtain a reconstructed image.

Abstract: The present disclosure discloses a method for drawing a cranial image trajectory. The method comprises: providing, by a processor, at least one trajectory pattern template for parts of a standard cranial anatomy; acquiring, by a radiation image device, at least one cranial image of a patient, superimposing, by the processor, the trajectory pattern template of each part of the standard cranial anatomy onto the corresponding position of the patient's cranial image, and acquiring the trajectory pattern of the cranial image; and if a deviation is determined between the shape of the respective structure on the trajectory pattern of the patient's cranial image and that of the trajectory pattern template of each part of the standard cranial anatomy, adjusting the shape of the corresponding trajectory pattern template in the cranial anatomy so as to be the same as the respective structure in the cranial image by the processor.

Abstract: A method of generating a body marker includes detecting a portion corresponding to a shape of an object shown in a medical image from a first body marker by comparing the shape of the object with the first body marker, generating a second body marker in which the portion detected from the first body marker has been emphasized, and outputting the second body marker.

Abstract: An intelligent control system for a detector comprises an external control module (110) and at least one group of data transmission and control modules (120), wherein the external control module (110) is used for controlling packet issuing and feedback message processing; a fifth interface (125) connected to the external control module (110) and used for packet transmission; a processing unit (128); at least one group of first type of interfaces (121) respectively connected to a detector (150) and used for transmitting a control packet of the detector (150); at least one group of second type of interfaces (122) respectively connected to the detector (150) and used for transmitting original data of the detector (150); a data pre-processing unit (129) for acquiring and forwarding the original data or pre-processing data of the detector (150); and a sixth interface (126) connected to the external control module (110) and used for transmitting the original data/pre-processing data of the detector (150).

Abstract: A control system includes a radiation emission apparatus and a radiographic imaging apparatus that generates image data by receiving radiation. A first apparatus of the radiation emission apparatus and the radiographic imaging apparatus includes a first timer that performs time measurement to periodically generate first time measurement information. A second apparatus of the radiation emission apparatus and the radiographic imaging apparatus includes a second timer that performs time measurement to periodically generate second time measurement information. The first apparatus includes an interface that transmits the first time measurement information to the second timer. At least one apparatus includes a hardware processor which adjusts the operation of the first or second timer based on adjustment conditions in a state where the second timer does not acquire the first time measurement information.

Abstract: Imaging systems and methods are provided for detecting objects that may be hidden under clothing, ingested, inserted, or otherwise concealed on or in a person's body. An imaging assembly, e.g., X-ray source and X-ray detector, and mechanisms, e.g., a translational mechanism for vertically moving the imaging assembly, may be configured to reduce the overall form factor of such imaging systems, while still retaining an ability to perform full/complete imaging of a subject.

Abstract: A stereoscopic endoscope apparatus includes: an image pickup device configured to pick up optical images for a right eye and a left eye; a similarity degree determination portion configured to receive input of an image signal for the right eye and an image signal for the left eye outputted from the image pickup device, and calculate a similarity degree between the image for the right eye and the image for the left eye; and an image signal output portion configured to switch and output a three-dimensional image signal formed of the image signal for the right eye and the image signal for the left eye and a two-dimensional image signal formed of either one of the image signal for the right eye and the image signal for the left eye, based on the similarity degree calculated by the similarity degree determination portion.

Abstract: A method is for generating image data using a computer tomography device. CT raw data is provided. An initial image is produced from the CT raw data. The initial image is segmented into regions based upon anatomical features. An image mask corresponding to the regions in each case is produced for the initial image, the image mask defining an effective region for a respectively assigned mapping rule. The mapping rules are applied in the effective regions defined by the respective image masks, and the image data is generated based upon the initial image processed via the mapping rules.

Abstract: A system for imaging an object via pre-shot processing is provided. The system includes an imaging device operative to image the object, and a controller in electronic communication with the imaging device. The controller is operative to acquire at least one pre-shot image of the object via the imaging device; and to generate, based at least in part on the at least one pre-shot image, an indicator that corresponds to a likelihood that one or more diagnostic images of the object acquired via the imaging device will be medically deficient.

Abstract: A system and method of processing an image is provided in which an input image output by an imaging sensor is received. For each location of a plurality of locations of a reference point of a moving window in the input image, a first image quality metric is determined as a function of quality of first image content included in a region covered by the moving window, wherein the window is sized to include at least a significant portion of a target of interest. An enhancement process is applied to the input image and generates a resulting enhanced image that is spatially registered with the input image. For each location of the plurality of locations of the reference point of the moving window in the enhanced image, a second image quality metric is determined as a function of quality of second image content included in the region covered by the moving window.

Abstract: The present application relates to the technical field of image recognition, and provides a carpal segmentation and recognition method, including: performing threshold segmentation on a carpal region of interest on a child orthotopic wrist X-ray image based on an adaptive threshold segmentation manner of variable threshold segmentation windows, and extracting edge information of the carpal region of interest based on an edge detection manner; combining a binarized image obtained by performing the threshold segmentation with the extracted edge information to obtain an initial segmentation image; performing carpal recognition on the initial segmentation image by using a carpal anatomy priori model to obtain an initial recognition image including information of each carpal bone; and performing boundary optimization on the initial recognition image, and outputting a carpal recognition image obtained after the boundary optimization is performed.

Abstract: An automatic medical image processing system includes a series of operation stages, each automating specifying the image processing parameters for processing medical images. In response to an image processing indicator, a first medical image is automatically identified, including determining a first image operation and image processing parameters, without user intervention. The first image operation is performed on the first medical image based on the image processing parameters. A second medical image is generated and transmitted to the client device to be presented therein. The client device displays a message prompting the user whether the user is satisfied with the second medical image. In response to a user input from the client device indicating that the user is unsatisfied with the second medical image, one or more remedial options are presented to allow the user selecting a remedial action to reprocess the first medical image.

Abstract: A method and system for 3D/3D medical image registration. A digitally reconstructed radiograph (DRR) is rendered from a 3D medical volume based on current transformation parameters. A trained multi-agent deep neural network (DNN) is applied to a plurality of regions of interest (ROIs) in the DRR and a 2D medical image. The trained multi-agent DNN applies a respective agent to each ROI to calculate a respective set of action-values from each ROI. A maximum action-value and a proposed action associated with the maximum action value are determined for each agent. A subset of agents is selected based on the maximum action-values determined for the agents. The proposed actions determined for the selected subset of agents are aggregated to determine an optimal adjustment to the transformation parameters and the transformation parameters are adjusted by the determined optimal adjustment.

Abstract: A system and method are provided for generating time resolved series of angiographic volume data having flow information integrated therewith. The method includes generating a series of 3D time-resolved vascular volumes from time resolved x-ray projection data and calculating blood velocity in the vascular volumes x-ray projection data to determine a rate of change of calculated contrast material arrival time at positions along the vascular volumes. The method also includes displaying the 3D time-resolved vascular volumes with a graphical indication of blood velocity in the vascular volumes.

Abstract: Systems, methods, and devices for determining relative and absolute positions and orientations of a detector and an inspection part of a CT system. In some cases positions/orientations of the detector and the inspection part can be defined, at least in part, by tilt angles relative to reference axes and/or planes defined by various combinations of the reference axes. In some embodiments, sensors coupled to the detector and to a stage assembly having the inspection part coupled thereto can be used to determine the tilt angles of the inspection part and the detector, respectively. Data from the sensors characterizing tilt angles of the detector and the inspection part can be used to adjust projectional radiographs of the inspection part to correct for the mechanical wobble of the stage. By using tilt data to adjust projectional radiographs, the quality of tomographic images and 3-dimensional reconstructions of the inspection part can be improved.

Abstract: A nuclear scanner includes an annular support structure (12) which supports a plurality of radiation detector units (14), each detector unit including crystals (52), tiles (66) containing an array of crystals, or modules (14) of tiles. The detector units define annular ranks of crystals, and the annular ranks of crystals define spaces between the ranks. In another embodiment, the crystals define axial spaces between crystals. Separate rings of crystals have axial spaces that are staggered such that no area of the imaging region is missed. The spaces between the detector units may be adjusted to form uniform or non-uniform spacing. Moving the patient through the annular support structure compensates for reduced sampling under the spaces between ranks.

Abstract: Ad. X-ray inspection apparatus includes a conveyance unit, an X-ray radiation unit, an X-ray detection, unit, and an image processing unit. The X-ray detection unit has a plurality of direct conversion-type X-ray detection element arrays disposed, side-by-side in rows along a direction intersecting both a conveyance direction in which an object is conveyed by the conveyance unit and a radiation direction in which X-rays are radiated by the X-ray radiation unit The image processing unit has an edge detection unit configured to carry out edge detection processing on an X-ray transmission image to generate an edge detected image, a horizontal direction gradation unit configured to carry out horizontal direction gradation processing on the edge detected image to generate a horizontal direction gradation linage, and a synthesizing unit configured to synthesize the X-ray transmission image and the horizontal direction gradation image to generate a post-processing X-ray transmission image.

Abstract: A radiographic image processing apparatus includes a hardware processor, which determines the intensity of an edge in a radiographic image obtained by radiographically imaging a subject, sets a weighting factor to be used in extracting a frequency component from the radiographic image according to a determination result of the edge intensity, extracts the frequency component from the radiographic image using the weighting factor having been set, multiplies the extracted frequency component by a scattered radiation content rate to estimate a scattered radiation component in the radiographic image, multiplies the estimated scattered radiation component by a scattered radiation removal rate to generate a scattered radiation image representing the scattered radiation component to be removed from the radiographic image, and performs scattered radiation correction on the radiographic image by subtracting the scattered radiation image from the radiographic image.

Abstract: Systems and methods are disclosed for determining anatomy directly from raw medical acquisitions using a machine learning system. One method includes obtaining raw medical acquisition data from transmission and collection of energy and particles traveling through and originating from bodies of one or more individuals; obtaining a parameterized model associated with anatomy of each of the one or more individuals; determining one or more parameters for the parameterized model, wherein the parameters are associated with the raw medical acquisition data; training a machine learning system to predict one or more values for each of the determined parameters of the parametrized model, based on the raw medical acquisition data; acquiring a medical acquisition for a selected patient; and using the trained machine learning system to determine a parameter value for a patient-specific parameterized model of the patient.

Abstract: The present disclosure provides a method and apparatus for building a text classification model, and a text classification method and apparatus. The method of building a text classification model comprises: obtaining a training sample; obtaining a vector matrix corresponding to the text, after performing word segmentation for the text based on an entity dictionary; using the vector matrix corresponding to the text and a class of the text to train a first classification model and a second classification model respectively; during the training process, using a loss function of the first classification model and a loss function of the second classification model to obtain a loss function of the text classification model, and using the loss function of the text classification model to adjust parameters for the first classification model and the second classification model, to obtain the text classification model formed by the first classification model and the second classification model.

Abstract: A method, a system and a terminal for identity authentication, and a computer readable storage medium are provided. The method includes: acquiring a human body image of a person to be authenticated, and determining from the human body image a plurality of skeleton key points of the person to be authenticated; converting the skeleton key points into feature data, and combining the feature data to form physique feature information characterizing the person to be authenticated; processing the physique feature information using a physique feature model by inputting the physique feature information into the physique feature model, to obtain a processing result; and recognizing the identity of the person to be authenticated based on the processing result of the physique feature model.

Abstract: This disclosure generally pertains to methods and systems for processing electronic data obtained from imaging or other diagnostic and evaluative medical procedures. Certain embodiments relate to methods for the development of deep learning algorithms that perform machine recognition of specific features and conditions in imaging and other medical data. Another embodiment provides systems configured to detect and localize medical abnormalities on medical imaging scans by a deep learning algorithm.

Abstract: The quality of thoracic X-rays is depends on the inspiration state of an imaged patient. If the lungs of a patient are not significantly inflated during a thoracic X-ray, tissue from surrounding organs can cause the image to become cloudier, and the lung parenchyma is not effectively shown. Thus, there is a reliance on a medical professional to ensure that the patient is in an appropriate posture and inspiration state at the point of image exposure. This can be difficult with patients suffering from chronic conditions, though. Therefore, this application discusses a means to assess the inspiration state using the position of rib bones, and the diaphragm line in the X-ray image. Thus, an accurate estimate of inspiration state can automatically be reported to a medical professional, before a patient leaves the examination room, allowing an X-ray to be retaken, if necessary.

Abstract: The present disclosure is directed toward systems and methods for generating a composite radiographic image that corrects effects of parallax distortion. A sequence of radiographic images—including a series of discrete exposures or image frames from a fluoroscopic procedure—may be acquired using a C-arm apparatus. An exemplary method may include receiving a plurality of radiographic image frames pertaining to a patient, identifying a region of interest on the image frames, cropping the region of interest from a plurality of image frames, selecting a plurality of sequential portions of cropped image frames, and stitching together the selected portions to form a composite image that corrects effects of parallax distortion and displaying a three-dimensional image of a part of the patient according to the orientation of the patient calculated from this two-dimensional intra-operative radiographic imaging information.

Abstract: Smart metrology methods and apparatuses disclosed herein process images for automatic metrology of desired features. An example method at least includes extracting a region of interest from an image, the region including one or more boundaries between different sections, enhancing at least the extracted region of interest based on one or more filters, generating a multi-scale data set of the region of interest based on the enhanced region of interest, initializing a model of the region of interest; optimizing a plurality of active contours within the enhanced region of interest based on the model of the region of interest and further based on the multi-scale data set, the optimized plurality of active contours identifying the one or more boundaries within the region of interest, and performing metrology on the region of interest based on the identified boundaries.

Abstract: An retinal vessel image enhancement method comprises: constructing a blood vascular dictionary; applying Frangi-based filtering to retinal vessel images, deciding blood vessels in a second image sub-block belong to wide or thin vessels by directional filtering, and setting residual error weight and residual error threshold of a vascular region; calculating inner products between the second image sub-block and each first image sub-block, selecting a first image sub-block with maximum inner product, and calculating its corresponding sparse coefficient; calculating residual error image, and calculating the residual error of the vascular region according to the residual error weight of the vascular region, when the residual error is greater than the residual error threshold, the residual error image is set as a second image sub-block, repeating and calculating residual error; reconstructing the second image sub-block according to the sparse coefficient, then restructuring each reconstructed second image sub-block

Abstract: The invention relates to a method for background removal from documents. The method includes obtaining an image of a document, performing a clustering operation on the image to obtain a plurality of image segments, and performing, for each image segment, a foreground/background classification to determine whether the image segment includes foreground. The method further includes obtaining an augmented image by combining the image segments that include foreground, and obtaining a background-treated image by cropping the image of the document, based on the foreground in the augmented image.

Abstract: The disclosed computer-implemented method may include generating color schemes. In some embodiments, the systems described herein may generate a color scheme by plotting non-linear curves through various planes that each represent an attribute of a color, selecting points on the curves, and generating colors from the values of the points. By generating colors schemes based on non-linear curves, the systems described herein may easily and efficiently generate aesthetically pleasing color schemes with colors predictably clustered in light and dark luminosities, facilitating the creation of user interfaces that are accessible to visually impaired users. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: Operating a medical X-ray apparatus to create a fluoroscopy includes capturing a first X-ray image of a vascular tree as a vascular mask, and segmenting the first X-ray image into at least one image area with the vascular tree and at least one image area without the vascular tree. An intensity of the first X-ray image for the image area with the vascular tree is ascertained as a vascular mask intensity. A second X-ray image of a medical component introduced into the vascular tree is created as a component image. An intensity of the second X-ray image for an image area with the medical component is ascertained as a component intensity. A ratio of component intensity and vascular tree intensity is calculated, and an overlay image with the first and the second X-ray image is generated depending on the calculated ratio of the vascular mask intensity and the component intensity.

Abstract: A radiation imaging apparatus for imaging a radiation image inputs an operation instruction from a user and performs display control of a screen that has an input region in which one or more information input regions for having various types of information input thereto are disposed, and a workflow region in which workflow information related to imaging of the radiation image is disposed. Here, when a confirmation instruction indicating confirmation of an operation is input, the radiation imaging apparatus moves the one or more information input regions of the input region toward a prescribed region of the workflow region, and performs display using animation that sequences the movement of the one or more information input regions.

Abstract: There is provided a method for predicting risk of osteoporotic fracture, comprising: receiving imaging data of a computed tomography (CT) scan of a body of a patient containing at least a bone portion, the CT scan being performed with settings selected for imaging of non-osteoporosis related pathology; processing the imaging data to identify the bone portion; automatically extracting features based on the imaging data denoting the identified bone portion; computing an osteoporotic fracture predictive factor indicative of the risk of developing at least one osteoporotic fracture in the patient, or the risk of the patient having at least one severe osteoporotic fracture, based on the extracted features, the predictive factor calculated by applying a trained osteoporotic fracture classifier to the extracted features, the osteoporotic fracture classifier trained from data from a plurality of CT scans performed with settings selected for imaging non-osteoporosis related pathology; and providing the predictive fact