Abstract: A component mounting machine including a camera configured to capture an image of a component held by a suction nozzle; and an image processing section configured to process the image captured by the camera, recognize the shape of the component, and measure shape data of the component; wherein, when the deviation amount of the measurement value of the shape data of the component exceeds the allowable value, the deviation amount of the measurement value of the shape data of the component is compared to a retry determination that is larger than the allowance value, and if the deviation amount of the measurement value of the shape data of the component exceeds the retry determination value, the component is determined to be abnormal and is discarded to a specified discard location.

Abstract: The present disclosure describes systems and processes, including processes in which first location data is received. Visual access to a first image corresponding to the first location data is provided, the first image including a roof structure of a building. A first computer input capable of signaling a designation from the user of a building roof structure location within the first image is provided. A designation of the building roof structure location within the first image is received. Responsive to receiving the designation of the building roof structure location, a second computer input capable of signaling user-acceptance of the building roof structure location within the first image is provided. Subsequent to receiving the user-acceptance confirming the designation of the building roof structure location, a report of the roof structure is provided.

Abstract: An image processing apparatus configured to acquire first registration information being registration information between a first image of interest, which is the first frame image in the frame image pair, and the first reference image; to acquire second registration information being registration information between a second image of interest, which is the second frame image in the frame image pair, and the second reference image; to acquire reference registration information being registration information between the first reference image and the second reference image; and to acquire third registration information being registration information between the first image of interest and the second image of interest, based on the first registration information, the second registration information and the reference registration information.

Abstract: A method of identifying a background type in a photograph includes extracting a background image from a photograph, feeding the background image into a first convolution neural network to obtain a first decision, extracting color features in the background image, transforming the color features into a two-dimensional color feature matrix, feeding the two-dimensional color feature matrix into a second convolution neural network to obtain a second decision by the one or more computer processors, extracting texture features in the background image, transforming the texture features into a two-dimensional texture feature matrix image by the one or more computer processors, feeding the two-dimensional texture feature matrix into a third convolution neural network to obtain a third decision, computing a hybrid decision based on the first decision, the second decision, and the third decision, and identifying a background type in the background image based on the hybrid decision.

Abstract: A dynamic analysis device including a hardware processor that generates, from each of a first chest dynamic image and a second chest dynamic image generated by radiographing dynamics of a chest at different times, a plurality of pieces of waveform information including at least waveform information indicating a respiratory state and waveform information indicating a heartbeat state; selects, from the second chest dynamic image, a comparative image to be compared with a reference image included in the first chest dynamic image, according to the generated plurality of pieces of waveform information; and subjects the reference image and the comparative image to a comparison analysis process.

Abstract: A system and method for automatically generating an appealing visual based on an original visual captured by a vehicle mounted camera are provided. A semantic image content and its arrangement in the original visual is computed; an optimization process is performed that improves an appeal of the original visual by making it more similar to a set of predetermined traits. The optimization process may include adding information to the original visual to generate an enhanced visual by adapting content from further visuals, and adapting iteratively a geometric parameter set of the enhanced visual to generate a certain perspective or morphing to improve an arrangement of semantics in the enhanced visual. The optimized parameter set may be applied to the enhanced visual. Post-processing may be conducted after applying the optimized parameter set using a set of templates to generate a final visual that may be output for immediate or later use.

Abstract: A method for volumetric segmentation in a plurality of planar medical images includes, receiving, at an electronic processor, the plurality of planar medical images. A boundary of a candidate structure in the plurality of medical images is generated using a segmentation model. A first planar medical image from the plurality of planar medical images is displayed on a display. A user input is received using a user interface indicating a region in the first planar medical image. A first planar contour of the candidate structure is generated. The region is compared to the boundary. Responsive to the region being at least partially within the boundary, the first planar medical image is re-displayed on the display showing the first planar contour of the structure, and a finding record for the candidate structure including the boundary is generated.

Abstract: The present disclosure provides an operating method of an automatic brain infarction detection system on magnetic resonance imaging (MRI), which includes steps as follows. Images corresponding to different slices of a brain of a subject are received from the MRI machine. The image mask process is performed on first and second images of the images. It is determined whether the cerebellum image intensity and the brain image intensity in the first image are matched. When the cerebellum image intensity and the brain image intensity are not matched, the cerebellar image intensity in the first image is adjusted. The first image is processed through a nonlinear regression to obtain a third image. A neural network identify an infarct region by using the first, second and third images that are cut.

Abstract: Provided is an endoscope system capable of preventing a detection target from being overlooked in the case of using an automatic detection function for the detection target, and an operation method for the endoscope system. A comparison processing unit 74 performs comparison processing of comparing first-diagnosis identification information acquired at a first diagnosis with second-diagnosis identification information acquired at a second diagnosis that is different from the first diagnosis. A notification control unit 76 performs, if a determination is made that there is a difference in a detection target between the first diagnosis and the second diagnosis as a result of the comparison processing, control to make a notification about an oversight of the detection target.

Abstract: Systems, devices, methods, and computer processing products for automatically checking for errors in segmentation (contouring) using heuristic and/or statistical evaluation methods.

Abstract: An apparatus and method for lane feature detection from an image is performed according to predetermined path geometry. An image including at least one path is received. The image may be an aerial image. Map data, corresponding to the at least one path and defining the predetermined path geometry is selected. The image is modified according to the selected map data including the predetermined path geometry. A lane feature prediction model is generated or configured based on the modified image. A subsequent image is provided to the lane feature prediction model for a prediction of at least one lane feature.

Abstract: A diagnostic system, method, and a computer-readable storage medium for determining a severity of a gastric condition, such as gastric cancer, in a subject are disclosed. The diagnostic system includes a processor that can obtain various images of a stomach of the subject including wavelength images and generate difference images from the wavelength images. The processor can compare the subject images with reference images representative of different severity levels of gastric cancer, or can input the subject images into a learned model trained using the reference images stored in the database to extract a feature pattern corresponding to a severity of gastric cancer to diagnose the subject as having a particular severity level of gastric cancer.

Abstract: Disclosed are systems, devices and methods for imaging and image-based sorting of particles in a flow system, including cells in a flow cytometer. In some aspects, a system includes a particle flow device to flow particles through a channel, an imaging system to obtain image data of a particle during flow through the channel, a processing unit to determine a property associated with the particle and to produce a control command for sorting the particle based on sorting criteria associated with particle properties, and an actuator to direct the particle into one of a plurality of output paths of the particle flow device in real-time.

Abstract: A method of photographing a subject includes storing a library of photographic scene designs in a computer memory, training a photographic scene detection model by a computer processing device using machine learning from sample portrait images comprising known photographic scenes defined in the library of photographic scene designs, capturing a production portrait photograph, using a digital camera, of a subject in a photographic scene that is defined by a photographic scene design in the library of photographic scene designs, automatically detecting the photographic scene in the production portrait photograph using the photographic scene detection model operating on one or more computer processors, and processing the production portrait photograph by an image processing system to personalize the photographic scene detected in the production portrait photograph.

Abstract: A blood vessel status evaluation method and a blood vessel status evaluation device are provided. The method includes: obtaining at least one angiography image corresponding to a target user; selecting a target image from the angiography image; determining a blood vessel type of the target user according to a distribution status of a target blood vessel pattern in the target image; establishing a blood vessel topology structure corresponding to the target blood vessel pattern which includes information of a width of a blood vessel in the target blood vessel pattern and information of an intersection of blood vessel in the target blood vessel pattern; and automatically analyzing a blood vessel status of the target user according to the blood vessel type and the blood vessel topology structure.

Abstract: A single composite image is generated by selecting a pixel value for each pixel in any one of a plurality of captured images having been consecutively captured. A motion vector between at least two captured images among the plurality of captured images is calculated. Correction processing is performed, based on a motion vector corresponding to a pixel of interest in the composite image, on the pixel of interest or a pixel near the pixel of interest. The correction processing is performed by updating, using a bright pixel value, a pixel value of at least one pixel in a group of pixels associated with a path from the pixel of interest to a pixel indicated by the motion vector corresponding to the pixel of interest.

Abstract: The invention relates to a method, an apparatus and a computer program product for encoding multicamera views. The method comprises determining a most probable viewing direction (MPVD) in a content; finding the location of the most probable viewing direction (MPVD) on all available views (View 1-View 8) of the content; defining one or more central locations for each available view (View 1-View 8); determining how the central locations cover the most probable viewing direction (MPVD) on each available view (View 1-View 8), and applying encoding to each view accordingly.

Abstract: Methods and systems for insertion of an instrument into a body cavity of an animal for performing a surgical procedure using a processor circuit controlled robotic surgery system are disclosed. In some embodiments, a method involves receiving body cavity image data representing an interior view of the body cavity captured by a camera inserted into the body cavity, determining, by the processor circuit, instrument parameters associated with physical extents of the instrument to be inserted, determining, by the processor circuit, an instrument envelope identifying a region through which the instrument is capable of moving in the body cavity, and generating, by the processor circuit, display signals operable to display a composite view of the interior of the body cavity on a display, the composite view being based on the body cavity image data and including an envelope overlay image generated to represent the instrument envelope.

Abstract: A system and method of image reconstruction is disclosed. First image scan data corresponding to a spiral CT modality received during a first time period is received. The first image scan data includes at least partially overlapping axial positions. A change in position over time for each of the at least partially overlapping axial positions is determined and a first respiratory waveform is estimated from the change in position over time for each of the at least partially overlapping axial positions.

Abstract: In an automated methodology for in vivo image-guided cell patch clamping, a cell patch clamping device is moved into position and targeted to a specific cell using automated image-guided techniques. Cell contact is determined by analyzing the temporal series of measured resistance levels at the clamping device as it is moved. The difference between successive resistance levels is compared to a threshold, which must be exceeded before cell contact is assumed. Pneumatic control methods are used to achieve gigaseal formation and cell break-in, leading to whole-cell patch clamp formation. An automated robotic system capable of performing this methodology automatically performs patch clamping in vivo, automatically locating cells through image guidance and by analyzing the temporal sequence of electrode impedance changes.