Abstract: The present disclosure provides a system and method for medical imaging. The method may include obtaining a preliminary image and scanning data of a subject acquired using a scanner. The method may also include determining a regularization parameter for a regularization item of an objective function based at least in part on the scanning data, wherein the regularization parameter includes at least two of a first component characterizing quality of the scanning data, a second component characterizing the scanner, or a third component characterizing a feature of the subject. The method may further include generating an image of the subject by reconstructing the preliminary image based on the objective function.

Abstract: Systems and methods for determining a current state, of at least one traffic light, for use in controlling an autonomous vehicle are described herein. Implementations determine, based on a pose instance of the autonomous vehicle and a stored mapping of an environment of the autonomous vehicle, a region of the environment includes the traffic light and a configuration that is assigned to the traffic light. Further, those implementations process an image capturing the region, using a machine learning classifier, to generate predicted output associated with multiple candidate states of the traffic light, and determine a current state of the traffic light based on the predicted output. Processing the image using the machine learning classifier can be based on the configuration of the traffic light.

Abstract: Aspects of the disclosure provide for systems and processes for assessing image quality for optical character recognition (OCR), including but not limited to: segmenting an image into patches, providing the segmented image as an input into a first machine learning model (MLM), obtaining, using the first MLM, for each patch, first feature vectors representative of a reduction of imaging quality in a respective patch, and second feature vectors representative of a text content of the respective patch, providing to a second MLM the first feature vectors and the second feature vectors, and obtaining, using the second MLM, an indication of suitability of the image for OCR.

Abstract: A text recognition method and apparatus disclosed. The text recognition method includes: obtaining a to-be-detected image; determining a target text detection area in the to-be-detected image, where the target text detection area includes target text in the to-be-detected image, and the target text detection area is a polygonal area including m vertex pairs, m being a positive integer greater than 2; correcting the polygonal area to m?1 rectangular areas to obtain a corrected target text detection area; and performing text recognition on the corrected target text detection area to determine the target text, and outputting the target text.

Abstract: An image-guided method and radio therapy device are provided. The method includes: acquiring a rotation offset, a planned image and a real-time image of a target object; and determining a tracking offset based on the rotation offset, the planned image and the real-time image, the tracking offset being used for tracking the target object; where the rotation offset is generated by a position difference of the target object in a planning stage and a treatment stage. The planned image of the target object is acquired in the planning stage. The tracking offset is determined based on the rotation offset, the planned image and the real-time image. The tracking of the target object based on the tracking offset compensates for image distortion caused by the deflection of the position of the target object in the planning stage and the treatment stage.

Abstract: A method for calculating a coronary artery calcium score, the method comprising acquiring a target image for a coronary artery and myocardium before contrast enhancement, identifying the coronary artery included in the target image by using an artificial neural network, calculating a coronary artery calcium score based on the identified coronary artery, wherein the artificial neural network is trained based on a training database generated via alignment between a pre-acquired image of a coronary artery and myocardium before contrast enhancement and a pre-acquired image of a coronary artery and myocardium after contrast enhancement.

Abstract: Techniques for updating data operations in a perception system are discussed herein. A vehicle may use a perception system to capture data about an environment proximate to the vehicle. The perception system may receive image data, lidar data, and/or radar data to determine information about an object in the environment. As different sensors may be associated with different time periods for capturing and/or processing operations, the techniques include updating object data with data from sensors associated with a shorter time period to generate intermediate object data.

Abstract: The present invention relates to the field of instruments for visualizing the inner structures of the human body, and in particular of the eye. More specifically, its object is an optical coherence tomography system and method of the “Fourier-domain” type with the removal of unwanted artifacts through digital image processing.

Abstract: A method for analyzing an anatomical structure of a patient may include the steps of receiving volumetric scan data representative of one or more features of an anatomical structure; mapping the features to a node tree diagram; and displaying the node tree diagram. The features can comprise branching points, pathways connecting the branching points, and location data of the branching points and pathways. The node tree diagram may comprise a plurality of nodes and branches representing the branching points and pathways in the anatomical structure, respectively. The plurality of nodes may comprise a root node representing a root branching point as well as additional nodes representing additional branching points. Additionally, the node tree diagram may comprise a first set of one or more regions, wherein each region encompasses a respective portion of the node tree diagram and is representative of a defined portion of the anatomical structure.

Abstract: Methods and systems of registering a model of one or more anatomic passageways of a patient to a patient space are provided herein. An exemplary method may include accessing a set of model points of the model of the passageways, the model points being associated with a model space, collecting measured points along a length of a catheter inserted into the passageways of the patient, the measured points determined by a shape of the catheter, and assigning points of the first set to a plurality of subsets. The exemplary method may further include registering each of the subsets with the model points to produce a plurality of registration candidates, comparing the candidates to identify an optimal subset associated with an optimal registration of the plurality of candidates that translates the set of model points and at least one set of the sets of measured points into a common space.

Abstract: A point data acquisition unit acquires point data indicating a reflection point obtained by an optical sensor that receives reflected light of an emitted light beam reflected at the reflection point. An image data acquisition unit acquires image data of an area around the reflection point indicated by the point data. A luminance calculation unit calculates smoothness of luminance of the image data. A fog determination unit determines the density of fog based on a distance, which is determined from the point data, from the optical sensor to the reflection point and the smoothness of the luminance.

Abstract: A method for detecting and labeling a target object in a 2D image includes receiving a plurality of 2D images from a visual sensor, manually marking points of the target object on each of the 2D images, generating from the 2D images a 3D world coordinate system of the environment surrounding the target object, mapping each of the marked points on the 2D images to the 3D world coordinate system using a simultaneous localization and mapping (SLAM) engine, automatically generating a 3D bounding box covering all the marked points mapped to the 3D world coordinate system, mapping the 3D bounding box to each of the 2D images, generating a label for the target object on each of the 2D images using a machine learning object detection model, and training the machine learning object detection model based on the generated label for the target object.

Abstract: Systems and methods are provided for three dimensional depth reconstruction of vessels in two dimensional medical images. A medical image comprising braches of one or more vessels is received. A branch overlap image channel that represents a pixelwise probability that the branches overlap is generated. A set of branch orientation image channels are generated. Each branch orientation image channel is associated with one of a plurality of orientations. Each branch orientation image channel representing a image channel represents a pixelwise probability that the branches are oriented in its associated orientation. A multi-channel depth image is generated based on the branch overlap image channel and the set of branch orientation image channels. Each channel of the multi-channel depth image comprises portions of the branches corresponding to a respective depth.

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: The present disclosure provides a method for correcting an OCR text position, a storage medium and an electronic device. The method includes: determining a first slope of each text block in an OCR recognition result of a to-be-processed image; fitting a tilt field function in accordance with the first slope of each text block; determining an offset value of each text block in accordance with the tilt field function; and correcting a position of each text block in accordance with the offset value.

Abstract: A computer system identifies a medical condition in a patient. A trained machine learning image generator is used to generate a set of training images based on three-dimensional patient imaging data, wherein each training image is labeled with a projection angle of the corresponding two-dimensional projection. Using the set of training images, a machine learning image classifier model is trained to identify patient rotation angles in x-ray images. X-ray images are processed with the machine learning image classifier model to identify patient rotation angles. A machine learning medical condition classifier model is trained to identify a medical condition using the labeled x-ray images. The machine learning medical condition classifier model determines an indication of the medical condition in a patient's x-ray image. Embodiments of the present invention further include a method and program product for identifying a medical condition in a patient in substantially the same manner described above.

Abstract: To determine the state of a subject person with a simple structure, an image determining device includes: an imaging unit that captures an image from a first direction, the image including the subject person; a first detector that detects size information from the image, the size information being about the subject person in the first direction; a second detector that detects position-related information, the position-related information being different from the information detected by the first detector; and a determining unit that determines the state of the subject person, based on a result of the detection performed by the first detector and a result of the detection performed by the second detector.

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 determining an abnormality in a medical device from a medical image is provided. The method for determining an abnormality in a medical device comprises receiving a medical image, and detecting information on at least a part of a target medical device included in the received medical image.

Abstract: A method for estimating a ventricular volume is provided and includes: obtaining a left ventricular mask image corresponding to a heart ultrasound image, where the left ventricular mask image is a binary image; finding 3 reference point pixels in the left ventricular mask image, where each of the reference point pixels has a first value, each of the reference point pixels is surrounded by N surrounding pixels, and the surrounding pixels of each of the reference point pixels include N1 first surrounding pixels with the first value and N2 second surrounding pixels with a second value; estimating a left ventricular volume corresponding to the heart ultrasound image based on the reference point pixels.