Motion compensated reconstruction is currently not well-suited for reconstructing the valve, the valve leaflets and the neighboring vascular anatomy of the heart. Blurring of the valve and the valve leaflets occurs. This may lead to wrong diagnosis. A new approach for motion compensated reconstruction of the valve and the related anatomy is presented in which an edge-enhancing step is performed to suppress blurring.

A computer-implemented method is provided for improving live video quality. The method comprises: (a) acquiring, using a medical imaging apparatus, a stream of consecutive image frames of a subject; (b) feeding the stream of consecutive image frames to a first set of denoising components, wherein each of the first set of denoising components is configured to denoise an image frame from the stream of consecutive image frames in a spatial domain to output an intermediate image frame; (c) feeding a plurality of the intermediate image frames to a second denoising component, wherein the second denoising component is configured to (i) denoise the plurality of the intermediate image frames in a temporal domain and (ii) generate a weight map; and outputting a final image frame with improved quality in both temporal domain and spatial domain based at least in part on the weight map.

A reconstructed volume of a region of patient anatomy is processed to reduce motion artifacts in the reconstructed volume. Autosegmentation of high-contrast structures present in an initial reconstructed volume is performed to generate a 3D representation of the high-contrast structures. 2D mask projections are generated by performing forward projection on the 3D representation, where each 2D mask projection includes location information indicating pixels that correspond to the high-contrast structures during the forward projection process. The acquired 2D projections are modified via in-painting to generate corrected 2D projections, where the acquired 2D projections are modified using information from the 2D mask projections. For example, pixels in the acquired 2D projections that are associated with high-contrast moving structures are replaced with low-contrast pixels. These corrected 2D projections are used to produce an improved reconstructed volume with fewer and/or less visually prominent motion artifacts.

A medical image diagnosis apparatus according to an embodiment of the present disclosure includes: a gantry, one or more columns, a processing circuitry, and, and a supporting and moving mechanism. The gantry includes an imaging system related to imaging a patient. The one or more columns are each configured to support the gantry so as to be movable in a vertical direction. The processing circuitry generates an image on the basis of an output from the imaging system. The supporting and moving mechanism is configured to support the patient from underneath, while being installed so as to be movable in a direction intersecting the moving direction of the gantry. The processing circuitry controls the moving of the supporting and moving mechanism.

Conventionally, systems and methods have been provided for manual annotation of anatomical landmarks in digital radiography (DR) images. Embodiments of the present disclosure provides system and method for anatomical landmark detection and identification from DR images containing severe skeletal deformations. More specifically, motion artefacts and exposure are filtered from an input DR image to obtain a pre-processed DR image and probable/candidate anatomical landmarks comprised therein are identified. These probable candidate anatomical landmarks are assigned a score. A subset of the candidate anatomical landmarks (CALs) is selected as accurate anatomical landmarks based on comparison of the score with a pre-defined threshold performed by a trained classifier. Position of remaining CALs may be fine-tuned for classification thereof as accurate anatomical landmarks or missing anatomical landmarks. The CALs may be further fed to the system for checking misalignment of any of the CALs and correcting the misaligned CALs.

A dynamic analysis system processes a dynamic image obtained by irradiation of a subject from a radiation irradiation apparatus and by dynamic imaging on dynamics of the subject detected by a detector. The dynamic analysis system includes a hardware processor that performs position correction of the dynamic image by eliminating an effect of displacement of the subject in a direction perpendicular to a detector plane.

Electromagnetically transparent conductive materials, in particular nanomaterials, are used in a sensor along with piezoelectric materials to detect the motion of a subject to provide respiratory and cardiac gating for imaging techniques such as MRI, CT scans and PET.

The present disclosure relates to a method for analyzing an R-wave of an electrocardiogram (ECG) signal. The method includes obtaining an original ECG signal of a subject; filtering the original ECG signal; determining whether to trigger a search gate based on the filtered ECG signal, wherein the search gate is an instruction for detecting an R-wave on the original ECG signal; and detecting the R-wave on the original ECG signal in response to a determination of triggering the search gate.

Methods and systems are provided for medical imaging systems. In one embodiment, a method for a medical imaging system comprises acquiring emission data during a positron emission tomography (PET) scan of a patient, reconstructing a series of live PET images while acquiring the emission data, and tracking motion of the patient during the acquiring based on the series of live PET images. In this way, patient motion during the scan may be identified and compensated for via scan acquisition and/or data processing adjustments, thereby producing a diagnostic PET image with reduced motion artifacts and increased diagnostic quality.

The following relates generally to motion prediction in magnetic resonance (MR) imaging. In some embodiments, a “modular” approach is taken to motion correction. That is, individual motion sources (e.g., a patient's breathing, heartbeat, stomach contractions, peristalsis, and so forth) are accounted for individually in the motion correction. In some embodiments, to correct for a particular motion source, a reference state is created from a volume of interest (VOI), and other states are created and deformably aligned to the reference state.