Abstract: Disclosed is a cross-view image optimizing method and apparatus, and a computer equipment and a readable storage medium.

Abstract: A system and method for model-based camera tracking and image occlusion removal for a camera viewing a sports field (or other scene) includes receiving a synthesized data set comprising at least one empty field image of the field, the empty field image with at least one occlusion graphic, and camera parameters corresponding to the empty field image, training a neural network model to estimate the empty field image and the corresponding camera parameters by providing the model with an input training image comprising the empty field image with occlusion graphic, and providing the model with model output targets comprising the empty field image and the corresponding camera parameters as targets for the model, receiving by the neural network model, alive input image comprising a view of the field with live occlusions, and providing by the neural network model, using trained model parameters, estimated live camera parameters or an estimated empty field image associated with the live input image.

Abstract: A method and apparatus for marking a target with a radiopaque marker is disclosed. The method may include providing a radiopaque filament and inserting at least portion of the radiopaque filament into tissue. The filament may extend continuously and at last partially around a perimeter of the target so that the filament is disposed in a plurality of surgical planes to demarcate the target with the radiopaque maker.

Abstract: Systems, methods, and computer software are disclosed for acquiring images during delivery of a radiation beam, the images capturing at least a portion of a shape representative of a radiation field generated by a radiation delivery system that includes a radiation source configured to deliver the radiation beam.

Abstract: A tomographic image processing apparatus including a display, an input interface configured to receive an external input, a storage storing an input tomographic image of an object, and at least one processor configured to control the display to display the input tomographic image, determine a material combination to be separated from the input tomographic image, and control the display to display material separation information corresponding to the determined material combination for a region of interest selected in the input tomographic image based on the external input. The input tomographic image is a spectral tomographic image having a plurality of tomographic images respectively corresponding to a plurality of energy levels.

Abstract: An ophthalmologic information processing apparatus includes an analyzer, a storage unit, a region editing unit, and a display controller. The analyzer is configured to analyze data of a subject's eye optically acquired by projecting light onto the subject's eye, and to specify a lesion region in the subject's eye. The storage unit stores image data of the subject's eye. The region editing unit is configured to specify a changed region by changing the lesion region based on operation information corresponding to an operation content on an operating unit. The display controller is configured to cause an image of the subject's eye to be displayed on a display means based on the image data stored in the storage unit, and to cause a region corresponding to the changed region in the image of the subject's eye to be displayed so as to be identifiable.

Abstract: In various examples, a system receives image data characterizing an image of an item. Additionally, the system implements a first set of operations and a second set of operations. In some examples, the first set of operations includes performing a structural similarity analysis of the item, based on the image data, and determining a structural similarity score based on the structural similarity analysis of the item. In other examples, the second set of operations includes generating a plurality of derivative images by applying a plurality of distortions to the image of the item, extracting one or more features based at least on the plurality of derivative images, and determining the quality of the image based at least on the extracted one or more features and the structural similarity score.

Abstract: A system and method for analyzing bodily fluid include a sample holder holding a bodily fluid sample, an image capture device generating an image of the bodily fluid sample comprising a plurality of fields of view. An image processor is programmed to determine a biofilm in the bodily fluid sample from the image, determine a biofilm area or volume within each of the plurality of fields of view to form a plurality of biofilm areas, determine a total biofilm area or total biofilm volume by adding the plurality of biofilm areas, determine a first value corresponding to a comparison of the total biofilm area or the total biofilm volume and a total volume of the bodily fluid sample, and classify the first value into a classification. An analyzer, using the classification, displays an indicator on a display for indicating the classification of the biofilm within the bodily fluid sample.

Abstract: A method of continuously registering a model of anatomic passageways to a patient space includes: collecting a set of measured points along a flexible catheter as the catheter is inserted into the passageways, the measured points based on a shape of the catheter; assigning each measured point to a respective subset of a plurality of subsets based upon a depth of each measured point within the passageways; comparing the plurality of subsets to identify a first optimal subset; registering the model to the patient space based on a set of model points and the first optimal subset; collecting additional measured points; updating the plurality of subsets by assigning each additional measured point to a respective subset; comparing, after the updating, the plurality of subsets to identify a second optimal subset; and registering the model to the patient space based on the set of model points and the second optimal subset.

Abstract: Techniques regarding mitigating bias in one or more machine learning models are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a model component that can evaluate a machine learning model at a plurality of threshold settings to generate a sample set and can define a relationship between a fairness metric and a utility metric of the machine learning model based on the sample set.

Abstract: Provided is a novel cell sheet evaluation method. A cell sheet evaluation method includes: a step of analyzing, based on an observed image of a cell sheet, a characteristic indicating shape uniformity of cells constituting the cell sheet; and a step of evaluating a binding state between cells in the cell sheet based on the analysis result.

Abstract: An electronic device may include a display layer including light transmissive portions and non-transmissive portions. The electronic device may also include a palm biometric image sensor layer beneath the display layer and configured to sense an image of a user's palm positioned above the display layer based upon light reflected from the user's palm passing through the light transmissive portions of the display layer. The electronic device may further include a controller configured to capture image data from the user's palm in cooperation with the palm biometric image sensor layer and determine a surface distortion of the user's palm based upon the image data. The controller may also be configured to perform a biometric authentication of the user's palm based upon the image data and the surface distortion.

Abstract: A pattern recognition system including an image gathering unit that gathers at least one digital representation of a field, an image analysis unit that pre-processes the at least one digital representation of a field, an annotation unit that provides a visualization of at least one channel for each of the at least one digital representation of the field, where the image analysis unit generates a plurality of image samples from each of the at least one digital representation of the field, and the image analysis unit splits each of the image samples into a plurality of categories.

Abstract: An image generation device includes: a detection unit 43 that performs processing of detecting a specific feature from a plurality of focus images which include an observation target and are in different focus states; a determination unit 44 that determines a parameter indicating a degree of application of a region image to a combination region image in a case where the combination region image is generated from the region image, for each set of the region images in a plurality of corresponding regions respectively corresponding to the plurality of focus images, based on the specific feature detected by the detection unit 43; and a generation unit 45 that generates the combination region image by combining the region images for each of the plurality of corresponding regions based on the parameter determined by the determination unit 44.

Abstract: A method includes assigning, to first voxels in a model of tissue of a chamber of a heart, respective first values of a parameter at respective locations on the tissue, the first voxels representing the locations, respectively. Some of the locations are on an endocardial surface of the tissue, and others of the locations are on an epicardial surface of the tissue. The method further includes assigning respective second values to second voxels in the model, a subset of which represent a portion of the tissue between the endocardial surface and the epicardial surface, by interpolating the first values. Other embodiments are also described.

Abstract: A method for optimizing an ultrasonic imaging system parameter based on deep learning, comprising the following steps: step 1: collecting samples for training neural networks, the samples comprising ultrasound image samples i, and a corresponding ultrasonic imaging system parameter vector sample p used by an ultrasonic imaging system when the ultrasonic image samples are collected; step 2: establishing a neural network model and training the neural networks to convergence by using the samples collected=in step 1, so as to obtain a trained neural network system onn; and step 3: taking the original ultrasonic imaging system parameter vector p or the original ultrasonic image as an input to be input into the neural network system onn trained in step 2, at this moment, a parameter obtained from an output end of onn being an optimized ultrasonic imaging system parameter vector ep=onn(p).

Abstract: Systems and methods are presented for providing a machine learning model for segmenting an optical coherence tomography (OCT) image. A first OCT image is obtained, and then labeled with identified boundaries associated with different tissues in the first OCT image using a graph search algorithm. Portions of the labeled first OCT image are extracted to generate a first plurality of image tiles. A second plurality of image tiles is generated by manipulating at least one image tile from the first plurality of image tiles, such as by rotating and/or flipping the at least one image tile. The machine learning model is trained using the first plurality of image tiles and the second plurality of image tiles. The trained machine learning model is used to perform segmentation in a second OCT image.

Abstract: The present disclosure is related to an optical encoder which is configured to provide precise coding reference data by feature recognition technology. To apply the present disclosure, it is not necessary to provide particular dense patterns on a working surface. The precise coding reference data can be generated by detecting surface features of the working surface.

Abstract: A colon cleanliness indicating device including a forward toilet-secured receiving section configured with a recessed receptacle for receiving colonic effluent and a rearward indicating section for indicating a degree of colon cleanliness. The indicating section is formed with one or more channels in fluid communication with the receptacle through which the received colonic effluent is flowable and by which the received colonic effluent can be visualized in order to assess a degree of colon cleanliness.

Abstract: A method, a controller, and a surgical hybrid navigation system for transferring a registration of three dimensional image data of a surgical object from a first to a second surgical navigation system are described. A first tracker that is detectable by a first detector of the first surgical navigation system is arranged in a fixed spatial relationship with the surgical object and a second tracker that is detectable by a second detector of the second surgical navigation system is arranged in a fixed spatial relationship with the surgical object. The method includes registering the three dimensional image data of the surgical object in a first coordinate system of the first surgical navigation system and determining a first position and orientation of the first tracker in the first coordinate system and a second position and orientation of the second tracker in a second coordinate system of the second surgical navigation system.