Disclosed is a medical system (100, 500) that comprises a radiotherapy system (102) configured for controllably irradiating a target volume (114) within an irradiation zone (112); a subject support (120) configured for supporting at least a ventral region (124) of a subject (122) within the irradiation zone; a breath monitor system (132, 132′) configured for providing a motion signal (154, 158) descriptive of subject breathing motion; and a subject display (130, 130′) configured for displaying a breathing phase indicator (160, 160′) to the subject when supported by the subject support. Execution of the machine executable instructions (150) causes a processor (142) controlling the medical system to receive (200) a time resolved magnetic resonance imaging dataset (152) synchronized to a measured motion signal (154). Execution of the machine executable instructions further causes the processor to repeatedly: determine (202) a desired motion signal (156) by temporally stepping through the measured motion signal; acquire (204) a current motion signal (158) using the breath monitor system; render (206) the breathing phase indicator on the display, wherein the breathing phase indicator is configured to indicate a difference (700) between the desired motion signal and the measured motion signal; and generate (208) control commands (162) configured for controlling targeting of the radio therapy system using a first portion of the time resolved magnetic resonance imaging dataset synchronized to the desired motion signal or a second portion of the time resolved magnetic resonance imaging dataset referenced by the current motion signal.

Methods and systems are provided for cardiac triggering of an imaging system. a method for an imaging system comprises acquiring, during a scan of a subject, an electrical signal indicating a periodic physiological motion of an organ of the subject, inputting a sample of the electrical signal into a trained neural network to detect whether a peak is present in the sample, triggering acquisition of image data responsive to detecting the peak in the sample, and not triggering the acquisition of image data responsive to not detecting the peak in the sample. In this way, the timing of data acquisition may be optimally and robustly synchronized with a cardiac cycle.

A medical device is configured to sense a cardiac electrical signal and determine from the cardiac electrical signal at least one of a maximum peak amplitude of a positive slope of the cardiac electrical signal and a maximum peak time interval from a pacing pulse to the maximum peak amplitude. The device is configured to determine a capture type of the pacing pulse based on at least one or both of the maximum peak amplitude and the maximum peak time interval.

A breathing guidance system is provided for guiding the breathing of a user during a magnetic resonance imaging procedure. A target breathing rate is determined for the user which is in synchronism with the sounds, such as clicking sounds, generated by the MRI scanner. In this way, an improved signal to noise ratio is obtained for the scanned image by controlling the breathing of the user to be regular.

Methods and systems are provided for cardiac computed tomography imaging. In one embodiment, a method comprises reconstructing an image from projection data acquired during a scan with a reconstruction time determined based on a model relating a timing of an event to be imaged to a heart rate measured during the scan. In this way, the timing of a reconstruction may be consistently applied for a series of reconstructions, thereby inherently registering the reconstructions.

A method for adapting, per cardiac cycle, the parameters governing interpolation of varying and non-interpolation of fixed fractions of each individual cardiac cycle is provided. A time series of data values associated with a cardiac cycle is received, and the time series is scaled to a reference cardiac cycle, wherein the scaling includes applying a model to the time series to generate a scaled time series of data values associated with the first cardiac cycle. The model is trained using the scaled time series.

A medical image diagnosis apparatus according to an embodiment includes processing circuitry. The processing circuitry is configured to derive a subject-specific regression model that indicates a relationship among a cardiac cycle, systole, and diastole of the subject. The processing circuitry is configured to derive timing of a data acquisition in a synchronization imaging performed in synchronization with heartbeats of the heart of the subject, by using the derived regression model and electrocardiographic information of the subject obtained during an image taking process. The processing circuitry is configured to control the synchronization imaging so that the data acquisition is performed with the derived timing.

A Cherenkov-based or thin-sheet scintillator-based imaging system uses a radio-optical triggering unit (RTU) that detects scattered radiation in a fast-response scintillator to detect pulses of radiation to permit capture of Cherenkov-light or scintillator-light images during pulses of radiation and background images at times when pulses of radiation are not present without need for electrical interface to the accelerator that provides the pulses of radiation. The Cherenkov images are corrected by background subtraction and used for purposes including optimization of treatment, commissioning, routine quality auditing, R&D, and manufacture. The radio-optical triggering unit employs high-speed, highly sensitive radio-optical sensing to generate a digital timing signal which is synchronous with the treatment beam for use in triggering Cherenkov light or scintillator light imaging.

The present invention involves positionally identifying several anatomical structures of interest of a patient's anatomy on images which have been acquired at different points of time. For each anatomical structure a separate image fusion transformation between these images is performed. For at least one of the image fusion transformations it is then determined whether this transformation is within a predetermined threshold, wherein for this determination, at least one further image fusion transformation of another anatomical structure is taken into account.

A method includes determining that a patient has heart failure with preserved ejection fraction (HFpEF); configuring a cardiovascular (CV) model using patient characterization data; determining one or more therapy parameters using output data of the CV model; and administering HFpEF therapy based on the one or more therapy parameters.