The present invention provides for a method for continuously monitoring a coupling quality of a coupling interface between an acoustic energy source of a therapeutic device and a body surface area of a patient, comprising the steps of: (f) obtaining a plurality of images of at least one predetermined first area of the coupling interface; (g) extracting at least one first image characteristic of a predetermined first image of said plurality of images; (h) extracting said at least one first image characteristic of at least one second image of said plurality of images, said at least one second image being temporally spaced apart from said predetermined first image; (i) determining a quantitative parameter corresponding to a difference between said at least one first image characteristic of said predetermined first image and said at least one first image characteristic of said at least one second image, and (j) actuating a signal if said quantitative parameter exceeds a predetermined reference threshold.

The present invention provides for a method for continuously monitoring a coupling quality of a coupling interface between an acoustic energy source of a therapeutic device and a body surface area of a patient, comprising the steps of: (f) obtaining a plurality of images of at least one predetermined first area of the coupling interface; (g) extracting at least one first image characteristic of a predetermined first image of said plurality of images; (h) extracting said at least one first image characteristic of at least one second image of said plurality of images, said at least one second image being temporally spaced apart from said predetermined first image; (i) determining a quantitative parameter corresponding to a difference between said at least one first image characteristic of said predetermined first image and said at least one first image characteristic of said at least one second image, and (j) actuating a signal if said quantitative parameter exceeds a predetermined reference threshold.

Systems and methods may be used for estimating instantaneous patient motion (a patient state). The patient state may be estimated based on a 3D reference volume and a stream of images, for example from an image acquisition device. The stream of images may be received in real-time, for example during a radiation therapy treatment. An example method may include encoding the 3D reference volume using a 3D encoder branch of a patient state generator network, encoding the stream of images using a 2D encoder branch of the patient state generator network, and combining the encoded 3D reference volume and the encoded real-time stream of images. The method may include estimating a 3D spatial transform that maps the 3D reference volume to a current patient state by decoding the combined encoding using a 3D decoder branch of the patient state generator network.

Systems and methods may be used for estimating instantaneous patient motion (a patient state). The patient state may be estimated based on a 3D reference volume and a stream of images, for example from an image acquisition device. The stream of images may be received in real-time, for example during a radiation therapy treatment. An example method may include encoding the 3D reference volume using a 3D encoder branch of a patient state generator network, encoding the stream of images using a 2D encoder branch of the patient state generator network, and combining the encoded 3D reference volume and the encoded real-time stream of images. The method may include estimating a 3D spatial transform that maps the 3D reference volume to a current patient state by decoding the combined encoding using a 3D decoder branch of the patient state generator network.

A system for monitoring vital signs includes: an imaging device for acquiring video image files of a living individual; a data analysis system including a processor and memory; a computer program running in the data analysis system to automatically analyze the video images, autonomously identify an area in the images where periodic movements associated with a selected vital sign may be detected and quantified; and, an interface that outputs an electrical signal corresponding to the waveform of the selected vital sign. The system may include a Graphical User Interface, which may display a visual graph of the waveform and a single video frame or a video stream of the individual.

A system for monitoring vital signs includes: an imaging device for acquiring video image files of a living individual; a data analysis system including a processor and memory; a computer program running in the data analysis system to automatically analyze the video images, autonomously identify an area in the images where periodic movements associated with a selected vital sign may be detected and quantified; and, an interface that outputs an electrical signal corresponding to the waveform of the selected vital sign. The system may include a Graphical User Interface, which may display a visual graph of the waveform and a single video frame or a video stream of the individual.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for deblurring an image captured by a robot-mounted camera. One of the methods comprises capturing, using a camera that is attached to an arm of a robot, an image at a first time, wherein the image exhibits motion blur, and wherein the exhibited blur was caused by movement of the arm of the robot at the first time; receiving, from a robot control system of the robot, motion data characterizing the movement of the arm of the robot at the first time; generating a motion kernel using the received motion data; and generating a deblurred image by processing the image using the motion kernel.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for deblurring an image captured by a robot-mounted camera. One of the methods comprises capturing, using a camera that is attached to an arm of a robot, an image at a first time, wherein the image exhibits motion blur, and wherein the exhibited blur was caused by movement of the arm of the robot at the first time; receiving, from a robot control system of the robot, motion data characterizing the movement of the arm of the robot at the first time; generating a motion kernel using the received motion data; and generating a deblurred image by processing the image using the motion kernel.

An apparatus for visualizing physical movements includes: a device for acquiring video image files; a data analysis system including processor and memory; a computer program operating in the processor to identify an area in the images where periodic motions associated with physical movement of an object may be detected and quantified, and compute a new image sequence in which the motions are visually amplified; and, a user interface that displays the motion-amplified video image of the mechanical component. An associated method for using the apparatus is also disclosed.

An apparatus for visualizing physical movements includes: a device for acquiring video image files; a data analysis system including processor and memory; a computer program operating in the processor to identify an area in the images where periodic motions associated with physical movement of an object may be detected and quantified, and compute a new image sequence in which the motions are visually amplified; and, a user interface that displays the motion-amplified video image of the mechanical component. An associated method for using the apparatus is also disclosed.