Abstract: A region extraction device and a method thereof in a stage previous to detection of a target object, capable of appropriately extracting a region having a possibility of presence of a target object emitting light having a light emission spectrum of a specific narrowband as a determination region in an imaging region, and an object detection apparatus and a method thereof capable of efficiently detecting the target object using a region extraction result are provided. In a region extraction method, a plurality of images including an image of a second narrowband corresponding to a first narrowband of light emitted by a target object and an image of a third narrowband different from the second narrowband are acquired from a multispectral camera.

Abstract: Systems and methods are disclosed for performing operations comprising: receiving a current fraction image and a reference image each depicting an anatomy of a subject, the reference image corresponding to a previous radiotherapy treatment fraction, the current fraction image corresponding to a current radiotherapy treatment fraction; obtaining a reference segmentation associated with the reference image; encoding, by a current fraction encoder, the current fraction image to generate a first set of features; encoding, by a reference encoder, the reference image and the reference segmentation to generate a second set of features; decoding, by a decoder, a combination of the first set of features and the second set of features to generate a predicted segmentation of the current fraction image; and configuring a radiotherapy treatment parameter based on the predicted segmentation of the current fraction image.

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: The present disclosure is generally related to systems and methods that can be implemented in a mobile application to allow users, such as parents and care providers, to measure and monitor, for example, a patient's body including an infant's head shape, at the point of care. The point of care can be, for instance, the home environment, a doctor's office, or a hospital setting. After acquiring 2D and/or 3D images of the body part, parameters reflecting potential deformity can be calculated. If abnormal measurements are determined, the user can be guided through therapeutic options to improve the condition. Based on the severity of the condition, different recommendations can be provided. Moreover, longitudinal monitoring and evaluation of the parameters can be performed. Monitoring of the normal child development can also be performed through longitudinal determination of parameters and comparison to normative values. Data can be shared with clinician's office.

Abstract: Disclosed are system, method, and computer program product embodiments for determining a digital marker indicative of a neurological condition. An embodiment operates by detecting a region of interest in an image frame of a face of a user. The region of interest includes an eye of the user and the image frame is obtained from a video stream. The embodiment then generates a point spread function (PSF) based on acquired data and a portion of the image frame specified by the region of interest, performs deconvolution on the portion of the image frame specified by the region of interest using the PSF, determines a set of oculometric parameters of the eye of the user using the deconvolved image, and determines one or more digital markers of the user based on the set of oculometric parameters. The one or more digital markers are indicative of a neurological condition of the user.

Abstract: A method and system to generate a probabilistic prediction of the presence/absence of cancer in longitudinal and current image datasets, and/or multimodal image datasets, and the location of the cancer, is described. The method and system uses an ensemble of deep learning models. The ensemble includes a global model in the form of a 3D convolutional neural network (CNN) extracting features in the datasets indicative of the presence of cancer on a global basis. The ensemble also includes a two-stage prediction model which includes a first stage or detection model which identifies cancer detection candidates (different cropped volumes of 3D data in the a dataset containing candidates which may be cancer) and a second stage or probability model which incorporates the longitudinal datasets (or multimodal images in a multimodal dataset) and the extracted features from the global model and assigns a cancer probability p to each of the cancer detection candidates.

Abstract: A method for imaging includes acquiring surface image data for a target using a first imaging modality. A visual representation of the target based on the surface image data is generated. Internal image data for the target is acquired using a second imaging modality. During acquisition of the internal image data, the visual representation of the target based on the acquired internal image data is updated.

Abstract: A method for training a depth estimation model and methods for use thereof are described. Images are acquired and input into a depth model to extract a depth map for each of the plurality of images based on parameters of the depth model. The method includes inputting the images into a pose decoder to extract a pose for each image. The method includes generating a plurality of synthetic frames based on the depth map and the pose for each image. The method includes calculating a loss value with an input scale occlusion and motion aware loss function based on a comparison of the synthetic frames and the images. The method includes adjusting the plurality of parameters of the depth model based on the loss value. The trained model can receive an image of a scene and generate a depth map of the scene according to the image.

Abstract: A method for constructing a three-dimensional representation of an internal surface of a conduit comprises obtaining a plurality of images of the internal surface of the conduit, for example from a camera mounted on an inspection tool, constructing, from the plurality of images, a composite image of the internal surface, providing a shape model of the internal surface, constructing, using the shape model, a three-dimensional mesh of the internal surface, and constructing a three-dimensional representation of the internal surface by assigning a pixel value from the composite image to a corresponding node of the mesh. The three-dimensional representation may be derived from two or more sets of images obtained under different image acquisition conditions, such as different camera angles, lighting conditions or spectral sensitivities.

Abstract: Methods, systems, and non-transitory computer readable media for computing physical dimensions of feet based on user-captured images are described. In at least one embodiment, an exemplary method comprises: receiving, by a server from a user device, an image of the user's foot or feet; segmenting the image to identify the user's foot or feet; computing the one or more physical parameters of the user's foot or feet.

Abstract: A classifier engine provides cell morphology identification and cell classification in computer-automated systems, methods and diagnostic tools. The classifier engine performs multispectral segmentation of thousands of cellular images acquired by a multispectral imaging flow cytometer. As a function of imaging mode, different ones of the images provide different segmentation masks for cells and subcellular parts. Using the segmentation masks, the classifier engine iteratively optimizes model fitting of different cellular parts. The resulting improved image data has increased accuracy of location of cell parts in an image and enables detection of complex cell morphologies in the image. The classifier engine provides automated ranking and selection of most discriminative shape based features for classifying cell types.

Abstract: A medical image processing apparatus including processing circuitry configured to: obtain from medical imaging measurements, observations of one or more vector or tensor valued fields as projected from one or more 2D acquisition planes; use an optimisation procedure to determine from the observations a superset of 3D fields (which may be scalar, vector, or tensor) via a solution ansatz constrained by a system of partial differential equations, and output the plurality of these fields.

Abstract: This invention belongs to measurement methods that can be used in light industry, when measuring the shape and size of the human body parts. Disclosed is a method, over the course of which, based on a series of photographs an image of a flat object of known shape and size is identified on each photograph. The body part area is isolated from the background in the image, and the area of an arbitrary body that does not belong to the projection of the human body part is cut out. Also disclosed is a method for searching an image of a flat object of known shape and size, its projection, and the camera location and orientation, over the course of which the predicted image of the flat object is compared to the real on. Here, the particle dynamics technique is used for isolating a human body part from the image background.

Abstract: Various embodiments of the present disclosure relate generally to systems and methods for drone-based systems and methods for capturing a multi-media representation of an entity. In some embodiments, the multi-media representation is digital, or multi-view, or interactive, and/or the combinations thereof. According to particular embodiments, a drone having a camera is controlled or operated to obtain a plurality of images having location information. The plurality of images, including at least a portion of overlapping subject matter, are fused to form multi-view interactive digital media representations.

Abstract: Provided are a three-dimensional reconstruction method, apparatus and system of a dynamic scene, a server and a medium. The method includes: acquiring multiple continuous depth image sequences of the dynamic scene, where the multiple continuous depth image sequences are captured by an array of drones equipped with depth cameras; fusing the multiple continuous depth image sequences to establish a three-dimensional reconstruction model of the dynamic scene; obtaining target observation points of the array of drones through calculation according to the three-dimensional reconstruction model and current poses of the array of drones; and instructing the array of drones to move to the target observation points to capture, and updating the three-dimensional reconstruction model according to multiple continuous depth image sequences captured by the array of drones at the target observation points.

Abstract: Techniques are provided for determining a cell count within a whole slide pathology image. The image is segmented using a global threshold value to define a tissue area. A plurality of patches comprising the tissue area are selected. Stain intensity vectors are determined within the plurality of patches to generate a stain intensity image. The stain intensity image is iteratively segmented to generate a cell mask using a local threshold value that is and gradually reduced after each iteration. A chamfer distance transform is applied to the cell mask to generate a distance map. Cell seeds are determined on the distance map. Cell segments are determined using a watershed transformation, and a whole cell count is calculated for the plurality of patches based on the cell segments. A client device may be configured for real-time cell counting based on the whole cell count.

Abstract: Provided are a method and an apparatus for interlocking a lesion location between a 2D medical image and 3D tomosynthesis images including a plurality of 3D image slices.

Abstract: A ripple push method for a graph cut includes: obtaining an excess flow ef(v) of a current node v; traversing four edges connecting the current node v in top, bottom, left and right directions, and determining whether each of the four edges is a pushable edge; calculating, according to different weight functions, a maximum push value of each of the four edges by efw=ef(v)*W, where W denotes a weight function; and traversing the four edges, recording a pushable flow of each of the four edges, and pushing out a calculated flow. The ripple push method explores different push weight functions, and significantly improves the actual parallelism of the push-relabel algorithm.

Abstract: Apparatuses, systems and methods are provided for generating and transmitting data representative of a vehicle operation mode. More particularly, apparatuses, systems and methods are provided for generating data representative of a vehicle operation mode based on vehicle interior image data.

Abstract: Described herein is a detector for determining a position of at least one object. The detector includes at least one sensor element having a matrix of optical sensors, the optical sensors each having a light-sensitive area, wherein the sensor element is configured to determine a reflection image of the object. The detector also includes an evaluation device configured to select a reflection feature of the reflection image, and determine a distance estimate of the selected reflection feature of the reflection image by optimizing at least one blurring function fa, wherein the distance estimate is given by a longitudinal coordinate z and an error interval ±?. The evaluation device is adapted to determine at least one displacement region in at least one reference image corresponding to the distance estimate, and to match the selected reflection feature with at least one reference feature within the displacement region.