Abstract: A moving body positioning device includes a sensor group that outputs a motion velocity vector of a moving body, a motion velocity vector estimation processing device that measures a motion velocity vector and outputs an output sequence of the motion velocity vector together with a measured time, a monitoring camera, an image analysis processing device that analyzes the image of the monitoring camera to measure a position of feet of the moving body measures a motion velocity vector at the position of the feet, and outputs an output sequence of the motion velocity vector with a measured time, and a motion velocity vector collation processing device that collates the output sequence of the motion velocity vector estimation processing device with the output sequence of the image analysis processing device and outputs its collation result as a TRUE or a FALSE signal.

Abstract: A method for correcting a volumetric image to address error due to deflection of a patient support is provided. The method includes obtaining a first set of projection data and a second set of projection data. The first and second sets of projection data are generated when the patient is at a first position and a second position, respectively, and are usable to reconstruct a first volumetric image and a second volumetric image, respectively. A corrected volumetric image is then determined based on the first and second sets of projection data.

Abstract: Methods and systems for locating a region of interest in an object are provided. One method includes acquiring planar nuclear medicine (NM) images of a subject from an NM system, wherein the planar NM images include at least one identified region of interest. The method also includes acquiring a three-dimensional (3D) x-ray Computed Tomography (CT) volume image of the subject from an x-ray CT system and locating the region of interest within the 3D CT volume image using the planar NM images.

Abstract: A method for functional visualization and localization of an arteriovenous malformation is proposed. A patient is scanned over a predetermined projection angle range during a contrast agent uptake time. The examination region is reconstructed using the projections over the entire projection angle range. The arteriovenous malformation is localized. The multiplicity of the projections is subdivided into at least three partial projection datasets each belonging to different consecutive time windows of the total duration of the scan. A time series having tomosynthesis image datasets is generated by the partial projection datasets. An arterial and/or venous assignment of the vessels flooded with contrast agent takes place based on the time series of tomosynthesis image datasets.

Abstract: Methods and apparatus for image matching using local features, in particular a method and apparatus for flexible interest point computation. The method involves producing multiple octaves of a digital image, wherein each octave of said multiple scale octaves comprises multiple layers; initiating a process comprising detection and description of interest points, wherein said process is programmed to progress layer-by-layer over said multiple layers of each of said multiple octaves, and to continue to a next octave of said multiple octaves upon completion of all layers of a current octave of said multiple octaves; upon the detection and the description of each interest point of said interest points during said process, recording an indication associated with said interest point in a memory, such that said memory accumulates indications during said process; and upon interruption to said process, returning a result being based at least on said indications.

Abstract: Removal of the effects of dust or other impurities on image data is described. In one example, a model of artifact formation from sensor dust is determined. From the model of artifact formation, contextual information in the image and a color consistency constraint may be applied on the dust to remove the dust artifacts. Artifacts may also be removed from multiple images from the same or different cameras or camera settings.

Abstract: An image signal processing apparatus, which includes a first area input-output characteristics control unit, which controls change of input-output characteristics for every arbitrary area associated with a value of an input luminance signal. The image signal processing apparatus also includes a second area input-output characteristics control unit, which controls change of input-output characteristics for every arbitrary area associated with an output of the first area input-output characteristics control unit, and a chrominance input-output characteristics control unit which controls the change of the input-output characteristics of an input chrominance signal by utilizing the output of the first area input-output characteristics control unit and the output of the second area input-output characteristics control unit.

Abstract: A method for facilitating an image guided medical procedure, utilizing images relating to the procedure, that includes performing a planning stage; performing an assessment stage; and performing an assessment stage via a unified workflow and user interface. The images relating to the procedure and extracted objects from the images are treated in the same manner so that image information from the stages may be combined for pre-, intra-, and post-procedural tasks.

Abstract: A vision system comprises a camera that captures an image and a processor coupled to process the received image to determine at least one feature descriptor for the image. The processor includes an interface to access annotated map data that includes geo-referenced feature descriptors. The processor is configured to perform a matching procedure between the at least one feature descriptor determined for the at least one image and the retrieved geo-referenced feature descriptors.

Abstract: An image processing apparatus includes a frame memory, a motion vector detector, a screen edge detector and an interpolation frame generator. The frame memory frame-delays an input signal and outputs the input signal as a delayed input signal. The motion vector detector detects a motion vector between frames based on the input signal and the delayed input signal. The screen edge detector detects a pixel corresponding to a screen edge in the input signal. The interpolation frame generator generates an interpolation frame from the input signal and delayed input signal based on the motion vector and the pixel corresponding to the screen edge. The interpolation frame generator generates the interpolation frame using the pixel corresponding to the screen edge or the pixel inside relative to the pixel corresponding to the screen edge when the motion vector points a pixel outside relative to the pixel corresponding to the screen edge.

Abstract: The disclosure provides an ultrasound image registration apparatus and a method thereof suitable for registering two ultrasound images partially overlapped with each other. The apparatus comprises: a first-stage image-developing processing module, a second-stage image-developing processing module and a registration module. The first-stage image-developing processing module performs beam-forming processing on two ultrasound images so as to generate two raw images. The second-stage image-developing processing module connects the first-stage module for performing envelope detection processing and compression processing on the raw images so as to generate two developed ultrasound images.

Abstract: What is disclosed is a non-contact system and method for determining cardiac function parameters from a vascular pattern identified from RGB and IR video signals captured simultaneously of a region of exposed skin of a subject of interest. In one embodiment, a video of a region of exposed skin is captured using a video camera that captures color values for pixels over visible channels and an IR camera that measures pixel intensity values in wavelength ranges of interest. Pixel intensity values are processed to generate a vascular binary mask that indicates pixel locations corresponding to the vascular pathways. The IR images are registered with corresponding data from the camera's visible channels such that pixels that correspond to the vascular pattern can be isolated in each frame of the video of visible color data. Once processed, pixels associated with the isolated vascular patterns are analyzed to determine desired cardiac function parameters.

Abstract: An object detecting device includes a camera ECU that detects an object from image data for a predetermined area has been captured by a monocular camera, a fusion processing portion that calculates the pre-correction horizontal width of the detected object, a numerical value calculating portion that estimates the length in the image depth direction of the calculated pre-correction horizontal width, and a collision determining portion that corrects the pre-correction horizontal width calculated by the fusion processing portion, based on the estimated length in the image depth direction.

Abstract: Psychovisual image compression techniques are disclosed that compress pixel data by a fixed compression ratio with little or no perceptual loss of detail. In some implementations, a psychovisual compression process is selected among several psychovisual compression processes based on characteristics of the pixel data. Compression is achieved during encoding by discarding psychovisually unnecessary bits from the pixel data. The psychovisual compression processes can be implemented in hardware and operate on scan lines of pixels captured by the image sensor. The psychovisual compression techniques can be used with image compression techniques to compress further the pixel data.

Abstract: Embodiments disclose systems and methods that aid in screening, diagnosis and/or monitoring of medical conditions. The systems and methods may allow, for example, for automated identification and localization of lesions and other anatomical structures from medical data obtained from medical imaging devices, computation of image-based biomarkers including quantification of dynamics of lesions, and/or integration with telemedicine services, programs, or software.

Abstract: Embodiments disclose systems and methods that aid in screening, diagnosis and/or monitoring of medical conditions. The systems and methods may allow, for example, for automated identification and localization of lesions and other anatomical structures from medical data obtained from medical imaging devices, computation of image-based biomarkers including quantification of dynamics of lesions, and/or integration with telemedicine services, programs, or software.

Abstract: A frame image is input. First to Nth intermediate images are generated from the frame image. First to Nth sub-filters that have been generated by dividing an original filter are held, along with relative position information of pixels referred to by each of the sub-filters. Pixel values are collected of pixels in an ith intermediate range (1?i?N). N sub-frame images are created by obtaining a pixel value of a pixel of interest in an ith sub-frame image from a calculation value obtained using the ith sub-filter with respect to the collected pixel values.

Abstract: The present invention utilizes depth images captured by a depth camera to detect foreground/background. The method comprises establishing a single background distribution model, updating the background distribution model if a new depth value for the pixel can be represented by the background distribution model, skipping update of the background distribution model if the pixel is before the background, and replacing the background distribution model if the pixel is behind the background. In case that the background distribution model does not exist initially, a new background distribution model is created. The fluctuation of the depth value due to noise is handled by using a candidate background distribution model. Furthermore, the noise for pixels around object edges is handled by using a mixture of two background distribution models.

Abstract: A therapeutic system, comprising: a MR imaging unit arranged to acquire MR signals from a patient in an examination volume, and a thermal treatment unit for depositing thermal energy within tissue of the patient. The system is arranged for: initiating a thermal treatment by heating the tissue at a focus within the examination volume selectively acquiring MR signals from a first image plane, including the focus, reconstructing a thermographic MR image from the MR signals acquired from the first image plane, computing a baseline thermographic MR image from a temperature distribution within at least one second image plane, moving the focus to a new position within the examination volume, changing the position and/or orientation of the first image plane corresponding to the new position of the focus, repeating the acquiring and reconstructing steps, wherein the baseline thermographic MR image is used for thermographic image reconstruction in a subsequent reconstructing step.

Abstract: The image signature extraction device includes an extraction unit and a generation unit. The extraction unit extracts region features from respective sub-regions in an image in accordance with a plurality of pairs of sub-regions in the image, the pairs of sub-regions including at least one pair of sub-regions in which both a combination of shapes of two sub-regions of the pair and a relative position between the two sub-regions of the pair differ from those of at least one of other pairs of sub-regions, and being classified into a plurality of types based on a combination of shapes of two sub-regions and a relative position between the two sub-regions of each of the pairs. The generation unit generates an image signature to be used for identifying the image based on the extracted region features of the respective sub-regions.