Abstract: An apparatus according to an embodiment includes a processing circuit. The processing circuit is configured to obtain first Doppler waveform data related to a left ventricular blood inflow. The processing circuit is configured to detect positions of an E-wave and an A-wave in the first Doppler waveform data, by using the first Doppler waveform data and a trained model trained with training data that includes at least positions of an E-wave and an A-wave in each of a plurality of pieces of second Doppler waveform data related to left ventricular blood inflows and the plurality of pieces of second Doppler waveform data.

Abstract: Various embodiments of an apparatus, methods, systems and computer program products described herein are directed to an agricultural observation and treatment system and method of operation. The agricultural treatment system may determine a first real-world geo-spatial location of the treatment system. The system can receive captured images depicting real-world agricultural objects of a geographic scene. The system can associate captured images with the determined geo-spatial location of the treatment system. The treatment system can identify, from a group of mapped and indexed images, images having a second real-word geo-spatial location that is proximate with the first real-world geo-spatial location. The treatment system can compare at least a portion of the identified images with at least a portion of the captured images. The treatment system can determine a target object and emit a fluid projectile at the target object using a treatment device.

Abstract: A computer-implemented method includes receiving a raw data set representing an image of a sample, identifying a first set of extremum by analyzing the raw data set using a metric algorithm, identifying a second set of extremum by analyzing the first set of extremum, and generating, based on the second set of extremum, a reconstructed image of the sample. A phase correcting scanner includes one or more processors, one or more scanner adapted to sequentially sample an object to generate a vector of raw data representing the object in a Lissajous pattern, and memory storing instructions that, when executed by the one or more processors, cause the computing system to receive the vector of raw data, identify a first set of extremum by analyzing the raw data set using a metric algorithm, and identify a second set of extremum by analyzing the first set of extremum.

Abstract: Breast image analysis systems and computer-implemented method for snip-triggered digital image report generation. An image review workstation of breast image analysis system presents an interactive user interface including a currently displayed image to a user through a display. Image review station receives user input selecting a snipping application of interactive user interface and activating a snipping application. A portion of currently displayed image is selected by execution of snipping application, and in response, image review workstation accesses a data store of acquired image files, identifies an acquired image file associated with currently displayed image, and generates a digital image report comprising the selected portion of the currently displayed image and selected metadata of the identified acquired image file and may also include user annotations such as spoken remarks and measurements and system generated data.

Abstract: An auto-exposure module determines a first set of exposure parameters to acquire a first image. The first image is acquired using the first set of exposure parameters. The module determines a target image histogram; calculates an image histogram based on intensity values of the pixels of the first image; determines an integral of the image histogram and of the target image histogram for a range of pixel intensity values; calculates a transfer curve for transforming the integral of the image histogram to match the integral of the target image histogram; calculates a slope of a line fitting at least a portion of the transfer curve; determines a correction factor based on the calculated slope; and adjusts the first set of exposure parameters according to the correction factor. A second image is then acquired using the adjusted first set of exposure parameters.

Abstract: A computing device obtains a to-be-processed video frame sequence of a first resolution. For each to-be-processed video frame in the to-be-processed video frame sequence, the computing device: (i) performs resolution reconstruction according to a resolution reconstruction model so as to obtain an initial reconstructed video frame of a second resolution, (ii) determines a contour region in the initial reconstructed video frame; and (iii) performs contour enhancement on the contour region to obtain a target reconstructed video frame. The computing device generates a reconstructed video frame sequence of the second resolution according to a plurality of target reconstructed video frames corresponding to the plurality of to-be-processed video frames.

Abstract: A method for decoding an image by a decoding device, according to the present document, comprises the steps of: acquiring image information; and generating a reconstructed picture on the basis of the image information.

Abstract: The present disclosure relates to techniques for segmenting and detecting cells within image data using transfer learning and a multi-task scheduler. Particularly, aspects of the present disclosure are directed to accessing a plurality of images of one or more cells, extracting three labels from the plurality of images, where the three labels are extracted using a Voronoi transformation, a local clustering, and application of repel code, training, by a multi-task scheduler, a convolutional neural network model based on three loss functions corresponding to the three labels, generating, by the convolutional neural network model, a nuclei probability map and a background probability map for each of the plurality of images based on the training with the three loss functions, and providing the nuclei probability map and the background probability map.

Abstract: A medical information processing apparatus according to an embodiment includes processing circuitry. The processing circuitry is configured to obtain medical images taken at a plurality of points in time. The processing circuitry is configured to obtain structures of a plurality of tissues, from medical images taken at a first point in time and at a second point in time different from the first point in time among the plurality of points in time. The processing circuitry is configured to calculate a measurement value related to a contact part between the plurality of tissues at the first point in time, on the basis of the obtained structures of the plurality of tissues at the second point in time and the obtained structures of the plurality of tissues at the first point in time.

Abstract: Embodiments of this invention provide a measurement map configuration method and apparatus. A wafer to be inspected is provided. The wafer includes a plurality of inspection marks. A first inspection result is obtained based on a first set of inspection marks. A second set of inspection marks is selected based on a preset rule. The second set of inspection marks is less than the first set of inspection marks. A second inspection result is obtained based on the second set of inspection marks. If an overlay accuracy of the second inspection result matches an overlay accuracy the first inspection result, a measurement map for the wafer is set based on target inspection marks. The target inspection marks are the second set of inspection marks of the measurement map.

Abstract: To improve pose estimation accuracy, a pose estimation apparatus according to the present invention extracts a person area from an image, and generates person area image information, based on an image of the extracted person area. The pose estimation apparatus according to the present invention further extracts a joint point of a person from the image, and generates joint point information, based on the extracted joint point. Then, the pose estimation apparatus according to the present invention generates feature value information, based on both of the person area image information and the joint point information. Then, the pose estimation apparatus according to the present invention estimates a pose of a person included in the image, based on an estimation model in which the feature value information is an input, and pose estimation result is an output.

Abstract: A method and apparatus for implementing scar tissue identification using a processor coupled to a memory is disclosed. The method and apparatus receive a first modality and a second modality. The first modality is of a first type. The second modality is of a second type, which is different from the first type. Each of the first modality and the second modality respectively describe organic tissue of a patient according to the first and second types. The method and apparatus cross reference the first modality and the second modality and generates improved image data for the first modality based on the cross referencing. The image data includes enhanced accuracy over or higher resolution than original data of the first modality.

Abstract: A method includes receiving intraoral scan data of an intraoral cavity of a patient; processing the intraoral scan data to determine, for each dental condition of a plurality of dental conditions, whether the dental condition is detected for the patient and a severity of the dental condition; and presenting indications of the plurality of dental conditions together in a graphical user interface (GUI), wherein the indications show, for each dental condition of the plurality of dental conditions, whether the dental condition was detected for the patient and the severity of the dental condition.

Abstract: A medical information processing apparatus according to an embodiment includes a processing circuitry. The processing circuitry is configured to: obtain first nerve activity information indicating an activity of a nerve of a subject; estimate first feeling information indicating a feeling experienced by the subject on the basis of the first nerve activity information; and determine presentation information to enable an evaluator to experience the feeling of the subject, on the basis of the first feeling information.

Abstract: Detection of synthetic content in portrait videos, e.g., deep fakes, is achieved. Detectors blindly utilizing deep learning are not effective in catching fake content, as generative models produce realistic results. However, biological signals hidden in portrait videos which are neither spatially nor temporally preserved in fake content, can be used as implicit descriptors of authenticity. 99.39% accuracy in pairwise separation is achieved. A generalized classifier for fake content is formulated by analyzing signal transformations and corresponding feature sets. Signal maps are generated, and a CNN employed to improve the classifier for detecting synthetic content. Evaluation on several datasets produced superior detection rates against baselines, independent of the source generator, or properties of available fake content.

Abstract: A medical image processing apparatus includes a recognition unit that detects a region of interest from a medical image and classifies the region of interest, a display control unit that causes emphasis display of the region of interest and a classification for the region of interest to be displayed in a screen for displaying the observation target, and a change determining unit that determines at least any of whether to change a display style of the emphasis display or whether to change a display style of the classification. The display control unit changes the display style of the emphasis display in the case where it is determined to change the display style of the emphasis display and changes the display style of the classification in the case where it is determined to change the display style of the classification.

Abstract: A method for assisting in cell isolation from a biological tissue section includes: obtaining cell images that are each an image of cells isolated from the biological tissue section, the biological tissue section being soaked in a solution containing an enzyme; calculating, from the cell images, a number of the cells isolated from the biological tissue section as an indicator of the cell isolation from the biological tissue section; and visualizing a temporal change in the indicator on the basis of a history of the indicator.

Abstract: An image processing apparatus comprises a first obtaining unit that obtains examination information, a readout unit that reads out learning result data selected based on the examination information from a storage unit storing at least one piece of learning result data that has been obtained by machine learning in advance, a second obtaining unit that obtains a medical image obtained based on the examination information obtained by the first obtaining unit, and a processing unit that processes the medical image obtained by the second obtaining unit using learning result data read out by the readout unit.

Abstract: Method and system for compensating intensity biases in a plurality of digital images. Each digital image of the plurality of digital images contains a plurality of objects and each of the plurality of objects is configured to receive at least one molecule comprising genetic information, wherein the at least one molecule is configured to receive one of at least a first fluorescent compound and a second fluorescent compound. A first digital image of the plurality of digital images is taken by an optical imaging system during emission of electromagnetic radiation by the first fluorescent compound, and a second digital image of the plurality of digital images is taken by the optical imaging system during emission of electromagnetic radiation by the second fluorescent compound.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.