Example aspects of the present disclosure describe a scene generator for simulating scenes in an environment. For example, snapshots of simulated traffic scenes can be generated by sampling a joint probability distribution trained on real-world traffic scenes. In some implementations, samples of the joint probability distribution can be obtained by sampling a plurality of factorized probability distributions for a plurality of objects for sequential insertion into the scene.

The present disclosure provides systems and methods for predicting a disease state of a subject using ultrasound imaging and ancillary information to the ultrasound imaging. At least two quantitative measurements of a subject, including at least one measurement taken using ultrasound imaging, as part of quantified information can be identified. One of the quantitative measurements can be compared to a first predetermined standard, included as part of ancillary information to the quantified information, in order to identify a first initial value. Further, another of the quantitative measurements can be compared to a second predetermined standard, included as part of the ancillary information, in order to identify a second initial value. Subsequently, the quantitative information can be correlated with the ancillary information using the first initial value and the second initial value to determine a final value that is predictive of a disease state of the subject.

Systems are provided for generating data representing electromagnetic states of a heart for medical, scientific, research, and/or engineering purposes. The systems generate the data based on source configurations such as dimensions of, and scar or fibrosis or pro-arrhythmic substrate location within, a heart and a computational model of the electromagnetic output of the heart. The systems may dynamically generate the source configurations to provide representative source configurations that may be found in a population. For each source configuration of the electromagnetic source, the systems run a simulation of the functioning of the heart to generate modeled electromagnetic output (e.g., an electromagnetic mesh for each simulation step with a voltage at each point of the electromagnetic mesh) for that source configuration. The systems may generate a cardiogram for each source configuration from the modeled electromagnetic output of that source configuration for use in predicting the source location of an arrhythmia.

Systems are provided for generating data representing electromagnetic states of a heart for medical, scientific, research, and/or engineering purposes. The systems generate the data based on source configurations such as dimensions of, and scar or fibrosis or pro-arrhythmic substrate location within, a heart and a computational model of the electromagnetic output of the heart. The systems may dynamically generate the source configurations to provide representative source configurations that may be found in a population. For each source configuration of the electromagnetic source, the systems run a simulation of the functioning of the heart to generate modeled electromagnetic output (e.g., an electromagnetic mesh for each simulation step with a voltage at each point of the electromagnetic mesh) for that source configuration. The systems may generate a cardiogram for each source configuration from the modeled electromagnetic output of that source configuration for use in predicting the source location of an arrhythmia.

An image fusion system provides a predicted alignment between images of different modalities and synchronization of the alignment, once acquired. A spatial tracker detects and tracks a position and orientation of an imaging device within an environment. A predicted pose of an anatomical feature can be determined, based on previously acquired image data, with respect to a desired position and orientation of the imaging device. When the imaging device is moved into the desired position and orientation, a relationship is established between the pose of the anatomical feature in the image data and the pose of the anatomical feature imaged by the imaging device. Based on tracking information provided by the spatial tracker, the relationship is maintained even when the imaging device moves to various positions during a procedure.

A patient interface for supplying a flow of breathable gas to the airways of a patient may comprise a heat and moisture exchanger (HME). The HME may be positioned in a flow path of the flow of breathable gas. The HME may absorb heat and moisture from gas exhaled by the patient and the incoming flow of breathable gas to be supplied to the patient's airways may be heated and moisturized by the heat and moisture held in the HME.

Systems and methods for training an artificial intelligence (AI) classifier of scanned items. The items may include a training set of sample raw scans. The set may include in-class objects and not-in-class raw scans. An AI classifier may be configured to sample raw scans in the training set, measure errors in the results, update classifier parameters based on the errors, and detect completion of training.

A structured 3D model of a real-world object is generated from a series of 2D photographs of the object, using photogrammetry, a keypoint detection deep learning network (DLN), and retopology. In addition, object parameters of the object are received. A pressure map of the object is then generated by a pressure estimation DLN based on the structured 3D model and the object parameters. The pressure estimation DLN was trained on structured 3D models, object parameters, and pressure maps of a plurality of objects belonging to a given object category. The pressure map of the real-world object can be used in downstream processes, such as custom manufacturing.

A computer implemented method of performing single pass optical character recognition (OCR) including at least one fully convolutional neural network (FCN) engine including at least one processor and at least one memory, the at least one memory including instructions that, when executed by the at least processor, cause the FCN engine to perform a plurality of steps. The steps include preprocessing an input image, extracting image features from the input image, determining at least one optical character recognition feature, building word boxes using the at least one optical character recognition feature, determining each character within each word box based on character predictions and transmitting for display each word box including its predicted corresponding characters.

A system that incorporates the subject disclosure may include, for example, a gaming system that cooperates with a graphical user interface to enable user modification and enhancement of one or more audio streams associated with the gaming system. In embodiments, the audio streams may include a game audio stream, a chat audio stream of conversation among players of a video game, and a microphone audio stream of a player of the video game. Additional embodiments are disclosed.