Abstract: For patient weight estimation in a medical imaging system, a patient model, such as a mesh, is fit to a depth image. One or more feature values are extracted from the fit patient model, reducing the noise and clutter in the values. The weight estimation is regressed from the extracted features.

Abstract: A method of deriving one or more medical scene model characteristics for use by one or more software applications is disclosed. The method includes receiving one or more sensor data streams. Each sensor data stream of the one or more sensor data steams includes position information relating to a medical scene. A medical scene model including a three-dimensional representation of a state of the medical scene is dynamically updated based on the one or more sensor data streams. Based on the medical scene model, the one or more medical scene model characteristics are derived.

Abstract: For patient weight estimation in a medical imaging system, a patient model, such as a mesh, is fit to a depth image. One or more feature values are extracted from the fit patient model, reducing the noise and clutter in the values. The weight estimation is regressed from the extracted features.

Abstract: A method for training a learning-based medical scanner including (a) obtaining training data from demonstrations of scanning sequences, and (b) learning the medical scanner's control policies using deep reinforcement learning framework based on the training data.

Abstract: Imaging from sequential scans is aligned based on patient information. A three-dimensional distribution of a patient-related object or objects, such as an outer surface of the patient or an organ in the patient, is stored with any results (e.g., images and/or measurements). Rather than the entire scan volume, the three-dimensional distributions from the different scans are used to align between the scans. The alignment allows diagnostically useful comparison between the scans, such as guiding an imaging technician to more rapidly determine the location of a same lesion for size comparison.

Abstract: A method for training a learning-based medical scanner including (a) obtaining training data from demonstrations of scanning sequences, and (b) learning the medical scanner's control policies using deep reinforcement learning framework based on the training data.

Abstract: A method for generating a nuclear image includes obtaining, via a camera, a surface image of a patient. A synthetic computed-tomography (CT) image of the patient is generated based on the surface image. First time-of-flight (TOF) data for the patient is obtained via a nuclear imaging modality. Attenuation correction is applied to the first TOF data. The synthetic image is applied as a density map during the attenuation correction. A nuclear image is generated from the attenuation corrected first TOF data.

Abstract: A method of deriving one or more medical scene model characteristics for use by one or more software applications is disclosed. The method includes receiving one or more sensor data streams. Each sensor data stream of the one or more sensor data steams includes position information relating to a medical scene. A medical scene model including a three-dimensional representation of a state of the medical scene is dynamically updated based on the one or more sensor data streams. Based on the medical scene model, the one or more medical scene model characteristics are derived.

Abstract: A method for device visualization includes receiving a set of physical characteristics including a description of spatial relationships of a plurality of markers within a device. Radiographic data of the device within a subject is acquired. An approximate location of each of the plurality of markers is identified within the radiographic data. A trajectory function is constructed for the device within the subject based on the identified approximate locations of each of the markers and the received set of physical characteristics. A section function is constructed for the device based on the set of physical characteristics and a 3D model is generated for the device based on the constructed trajectory function and the section function. A rendering of the 3D model is displayed on a display device.

Abstract: Localization of a coil is provided for magnetic resonance (MR)-guided intervention. A multi-scale decomposition and characteristic transitions in the power spectra for the coil are used to determine a distribution of likelihood of the coil being at each of various locations and/or to determine a confidence in the position determination. For example, the power spectra along each axis is used to generate a likelihood distribution of the location of the coil. The power spectra are decomposited at different scales. For each scale, the modulus maxima reflecting transitions in the power spectra are matched using various criteria. A likelihood is calculated for each of the matched candidates from characterizations of the matched candidates. The likelihood distribution is determined from a combination of the likelihoods from the various scales.

Abstract: In a method of real-time 3-D visualization and navigation for interventional procedures a position is determined at which data will be acquired, and data is acquired at the position. Features are extracted from the acquired data. A model described by the extracted features is built or updated, wherein updating the model includes calculating at least one acquisition parameter of a set of acquisition parameters. 3-D scenes showing the interior or exterior of one or more organs are displayed using the model or data extracted from the model. A region for updating is determined.

Abstract: Automatic measurement of morphometric and motion parameters of a coronary target includes extracting reference frames from input data of a coronary target at different phases of a cardiac cycle, extracting a three-dimensional centerline model for each phase of the cardiac cycle based on the references frames and projection matrices of the coronary target, tracking a motion of the coronary target through the phases based on the three-dimensional centerline models, and determining a measurement of morphologic and motion parameters of the coronary target based on the motion.

Abstract: A method for device visualization includes receiving a set of physical characteristics including a description of spatial relationships of a plurality of markers within a device. Radiographic data of the device within a subject is acquired. An approximate location of each of the plurality of markers is identified within the radiographic data. A trajectory function is constructed for the device within the subject based on the identified approximate locations of each of the markers and the received set of physical characteristics. A section function is constructed for the device based on the set of physical characteristics and a 3D model is generated for the device based on the constructed trajectory function and the section function. A rendering of the 3D model is displayed on a display device.

Abstract: A system receives an image volume of a patient. A catheter applied to the patient contains at least one sensor, which may be a microcoil and which is detectable in the image volume. A size and a shape of a region of interest are pre-defined. A processor determines a location of the at least one sensor in the image volume. The image volume is generated by a medical imaging device. The processor defines the shape and size of the region of interest relative to the location of the at least one sensor to determine the region of interest in the image volume. Image data of the region of interest in the image volume and of the region of interest in a previous image volume are registered. The region of interest is determined during an interventional procedure on the patient.

Abstract: A computer implemented method for automatically updating a geometric model of an object of interest includes determining, automatically, a region of the geometric model for updating according to a update parameter, acquiring data at the region, extracting features from the acquired data, updating the geometric model described by the extracted features, wherein updating the model includes calculating at least one acquisition parameter of a set of acquisition parameters, and displaying a scene showing the object of interest using the model.

Abstract: Apparatus for remotely controlling parameters of an image scanning apparatus includes a software interface for translating commands from an external application for providing scanner control commands to a scanner control machine for control of the parameters; and the software interface includes syntax software for translating the commands from the external application into a given syntax for providing the scanner control commands.

Abstract: Progress monitoring of lesions is done automatically by segmentation and registration of lesions in multi-phase medical images. A parametric level-set framework includes a model optimization for any number of lesions. The user specifies lesions in a baseline volume by clicking inside of them. The apparatus segments the lesions automatically in the baseline and follow-up volumes. The segmentation optimization compensates for lesion motion between baseline and follow-up volumes. 2D and 3D medical patient data can be processed by the methods.

Abstract: A method (100) of blood vessel extraction for rotational angiographic X-ray sequences, comprising obtaining a 2.5D vesselness detection response in 3D (208). The method (100) utilizes the projection matrices to realize the correspondence among different image frames to extract low level image features for subsequent segmentation and 3D image reconstruction.

Abstract: Automatic measurement of morphometric and motion parameters of a coronary target includes extracting reference frames from input data of a coronary target at different phases of a cardiac cycle, extracting a three-dimensional centerline model for each phase of the cardiac cycle based on the references frames and projection matrices of the coronary target, tracking a motion of the coronary target through the phases based on the three-dimensional centerline models, and determining a measurement of morphologic and motion parameters of the coronary target based on the motion.

Abstract: Apparatus for remotely controlling parameters of an image scanning apparatus includes a software interface for translating commands from an external application for providing scanner control commands to a scanner control machine for control of the parameters; and the software interface includes syntax software for translating the commands from the external application into a given syntax for providing the scanner control commands.