Abstract: The present invention provides a cell evaluation device, a cell evaluation method and a non-transitory computer readable recording medium storing a cell evaluation program capable of evaluating an evaluation target cell. The cell evaluation device includes an image acquisition unit that acquires a cell image obtained by imaging a cell group; a cell evaluation unit that specifies an evaluation target cell and peripheral cells around the evaluation target cell in the cell group, and evaluates the evaluation target cell based on evaluation results of the peripheral cells; and a boundary setting unit that sets a boundary in the cell image based on a state of the cell group, in which when specifying the peripheral cells, the cell evaluation unit specifies only cells that are present in a divided region where the evaluation target cell is present among plural divided regions divided by the boundary, as the peripheral cells.

Abstract: A method for generating fluid flow images of a region of interest is disclosed. The method includes: scanning the region of interest to acquire a set of 4D-Flow magnetic resonance images, wherein the set comprises an anatomical magnitude image, a first velocity component image, a second velocity component image, and a third velocity component image; isolating the anatomical magnitude image, the first velocity component image, the second velocity component image, and the third velocity component image from the set of 4D-Flow magnetic resonance images; converting the first, second, and third velocity component images into a velocity vector field; modeling a location of an anatomical wall within the region of interest; calculating at least one flow dynamics parameter for the region of interest; and generating a visual representation of the anatomical wall and the at least one flow dynamics parameter.

Abstract: A method for the reconstruction of planning images is based on a plurality of first respiratory cycles of a patient and tomographic raw data recorded at the same time as the first respiratory cycles being received. A reference cycle is determined based on respiratory cycles of the patient, in particular based on the first respiratory cycles of the patient. A reference cycle is subdivided into temporally equidistant reference phases, a reference amplitude being associated with each reference phase. The reference amplitudes are not equidistantly scanned therefore. Furthermore, the first respiratory cycles of the patient are subdivided into first phases, the temporal positions of the first phases each being based on one of the reference amplitudes. Reconstruction of planning images based on first intervals of the raw data follows, wherein the first intervals correspond to the first phases.

Abstract: A method of segmenting images of biological specimens using adaptive classification to segment a biological specimen into different types of tissue regions. The segmentation is performed by, first, extracting features from the neighborhood of a grid of points (GPs) sampled on the whole-slide (WS) image and classifying them into different tissue types. Secondly, an adaptive classification procedure is performed where some or all of the GPs in a WS image are classified using a pre-built training database, and classification confidence scores for the GPs are generated. The classified GPs with high confidence scores are utilized to generate an adaptive training database, which is then used to re-classify the low confidence GPs. The motivation of the method is that the strong variation of tissue appearance makes the classification problem more challenging, while good classification results are obtained when the training and test data origin from the same slide.

Abstract: A method of improving diagnostic and functional imaging is provided by obtaining at least two input images of a subject, using a medical imager, where each input image includes a different contrast, generating a plurality of copies of the input images using non-local mean (NLM) filtering, using an appropriately programmed computer, where each input image copy of the subject includes different spatial characteristics, obtaining at least one reference image of the subject, using the medical imager, where the reference image includes imaging characteristics that are different form the input images of the subject, training a deep network model, using data augmentation on the appropriately programmed computer, to adaptively tune model parameters to approximate the reference image from an initial set of the input and reference images, with the goal of outputting an improved quality image of other sets of low SNR low resolution images, for analysis by a physician.

Abstract: A medical imaging apparatus includes a scanner configured to acquire projection data of an object in a plurality of directions, and a data processor configured to generate a volume of interest based on the projection data, generate a two-dimensional (2D) reprojection image by reprojecting the volume of interest in at least one direction, and extract feature information from the 2D reprojection image.

Abstract: A method for correcting a CT scan image is provided. A target image including a target region to be corrected is extracted from an original CT scan image. A target projection range corresponding to the target region is obtained by orthographically projecting the target image, and target projection data within the target projection range is corrected. Noise of the corrected target projection data is adjusted to generate noise-adjusted target projection data to improve noise consistency between target region and the rest of the CT scan image. A corrected CT scan image is reconstructed based on the noise-adjusted target projection data.

Abstract: In an approach to tracking markers in one or more images, one or more computer processors identify objects that exist in more than one image from a plurality of images. The one or more computer processors analyze the identified objects for one or more physical characteristics. The one or more computer processors assign a marker to at least one object of the identified objects on at least one image of the more than one image, wherein the marker is annotated based upon the one or more physical characteristics of the object of the identified objects. The one or more computer processors store the more than one images, analysis data, and marker data associated with the identified objects and one or more markers. The one or more computer processors manipulate the one or more images based on a change in the objects across the more than one image.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing a CT (Computed Tomography) image are provided. An example method includes accessing an original CT image that is reconstructed from a first set of raw data and includes windmill artifacts, generating a high-frequency image by processing the original CT image, generating a low-frequency image by processing a plurality of thick images reconstructed from a second set of raw data and combining the plurality of processed thick images, the second set of raw data including the first set of raw data and each of the plurality of thick images including substantially no windmill artifacts, generating an intermediate image by synthesizing the high-frequency image and the low-frequency image, and obtaining a target CT image based on the generated intermediate image.

Abstract: Various systems and methods for implementing skin texture-based authentication are described herein. A system comprises a capture module to obtain at a wearable device worn by a user, an input representation of the user's skin; an analysis module to identify a set of features in the input representation; and an authentication module to authenticate the user based on the set of features.

Abstract: Systems and methods for predicting shape are provided. A system for predicting shape can include a database, a training analysis module, a subject analysis module, and a prediction module. The database can store two sets of training models characterized by first and second parameters, respectively (e.g., bone and cartilage), as well as a subject model characterized by the first parameter (e.g., a bone model). The relationships between these models can be determined by a training analysis module and a subject module. Based on these relationships, the prediction module can generate a predicted shape characterized by the second parameter (e.g., a predicted cartilage model corresponding to the bone model).

Abstract: Intra-oral imaging apparatus and/or method embodiments can provide digital dental reflectance images used to identify selected areas of interest (AOI) within a dental region of interest (ROI) having selected image characteristics for both hemoglobin's total concentration and oxygenation level. In one embodiment, reflectance images can determine relative total hemoglobin using at least a wavelength band that includes an isobestic wavelength for absorption coefficients of oxyhemoglobin (HbO2) and deoxyhemoglobin (Hb).

Abstract: A method and a system for registering multi-modal brain images includes registering two or more full volumes of brain images based on a projection based reference image. The registration is based on sharing of mass in a predetermined direction such as axial, sagittal and coronal direction. After the registration of two or more brain images, a two or more partial volumes in a region of interest is registered through a modified mutual information. The modified mutual information may be a factor of an overlap rate and a weight assigned to it.

Abstract: A method of detecting defects of a photomask includes measuring registration errors of the photomask, correcting the measured registration errors using a registration control process with a laser beam, extracting deformation data of the photomask deformed by the registration control process, reflecting the extracted deformation data in defect detection parameters to obtain compensated defect detection parameters, and detecting defects of the photomask using the compensated defect detection parameters.

Abstract: A rapid screening device has a sensing unit, a processing unit and a carrier, the processing unit is connected to the sensing unit, the sensing unit and the processing unit are disposed on the carrier, the sensing unit captures an image of an eyeball and outputs an image signal of the eyeball, the image of the eyeball is resolved from the image signal of the eyeball, the processing unit retrieves a plurality of images from the sensing unit within a predetermined time interval and executes an algorithm to generate a calculated result by the images of the image signals of the eyeball, and the calculated result is used to diagnose or predict a disease.

Abstract: A method for acquiring raw data for generating image data of a target organ via a magnetic resonance system is described. In an embodiment, test raw data is initially acquired from a measurement region including at least the target organ using a plurality of magnetic resonance coils. Test image data is reconstructed from the test raw data. Furthermore, a mask defining the position and the dimensions of the target organ is generated using the reconstructed test image data. The magnetic resonance coils, to be used for the image acquisition, are then selected. This takes place on the basis of intensity values from a region covered by the mask and intensity values of a measurement region lying outside of the mask. Finally, the measurement is performed by acquiring raw data via the selected magnetic resonance coils. Furthermore, a device for acquiring raw data for generating image data is also described.

Abstract: An exemplary system, method and computer-accessible medium for generating a magnetic resonance (MR) image(s) and a positron emission tomography (PET) image(s) of a tissue(s) can be provided, which can include, for example, receiving information related to a combination of MR data and PET data as a single data set, separating the information into at least two dimensions, at least one first of the dimensions corresponding to the MR data and at least one second of the dimensions corresponding to the PET data, and generating the MR image(s) and the PET image(s) based on the separated information.

Abstract: Aspects of this disclosure include a system for providing non-contact, computer-vision based monitoring of the health and pollination activity of a beehive. The system may include camera positioned proximate to a beehive. The camera may include an onboard processor that analyzes video of the beehive captured by the camera and calculates an activity value that estimates a number of bees moving about the beehive. The video calculated activity values may be uploaded to a server where they can be accessed via a user device. The user device may allow the user to display interactive plots of the activity values over a variety of time bases. The disclosed beehive monitoring system relies on relatively lost-cost hardware and requires neither modification to the hive nor special constraints on the placement of the camera.

Abstract: Platforms and techniques are described in which a traffic event detection system includes a camera connected to a CPU in a vehicle. The camera is mounted on an extendable support, and captures images in front of the vehicle at a height generally above that of vehicles that may be ahead of the subject vehicle. The CPU can analyze those images for sudden change in traffic pattern based on a change in red color content of the image stream, and can warn the driver with an alert if the cars in front of him or her brake suddenly, or other traffic events occur. In implementations, short-term and long-term signal averages can be used to reduce false positive signals, and increase overall accuracy of traffic detection processing. In embodiments, the system can apply a timer to determine if potential hazards continue to be detected, and generated louder alarms or other graduated alerts.

Abstract: Dimensions of a surface feature are determined by capturing an image of the surface feature and determining a scale associated with the image. Structured light may be projected onto the surface, such that the position of structured light in the captured image allows determination of scale. A non-planar surface may be unwrapped. The surface may alternatively be projected into a plane to correct for the scene being tilted with respect to the camera axis. A border of the surface feature may be input manually by a user. An apparatus and system for implementing the method are also disclosed.