Abstract: A method for operating an X-ray imaging system includes outputting first X-ray beams onto an X-ray detector by an X-ray source for acquisition of a first X-ray capture of an object under examination. The object under examination is arranged between the X-ray source and the X-ray detector and is passed through by the first X-ray beams. The X-ray detector acquires an entry dose of the first X-ray beams after passage through the object under examination. A parameter value of at least one parameter for output of second X-ray beams by the X-ray source for acquisition of a second X-ray capture of the object under examination is ascertained by a control system. The parameter value is ascertained by the control system according to a specified ascertainment method as a function of a foreground substance of a foreground object, a background substance of a background object, and the entry dose.

Abstract: Embodiments of the present invention include generating a 3D model of a body cavity, and receiving, from a position transducer associated with a medical probe configured to be inserted into the cavity and having at least one elongated electrode disposed along a distal end of the probe, signals indicating orientation and location coordinates of the distal end within the body cavity. Based on the model and the signals, while parts of the given electrode other than the identified segment are not in contact with the inner surface of the cavity, a segment along a length of a given electrode that is in contact with tissue at a site on an inner surface of the cavity is identified. A graphical representation of the model with a visual marker at a location on the model corresponding to the site contacted by the segment of the given electrode is rendered to a display.

Abstract: A system and method comprises execution of a segmented magnetic resonance imaging pulse sequence, the pulse sequence including a plurality of shots, each of the plurality of shots including an inversion recovery preparation pulse and acquiring a respective segment of k-space lines, wherein each shot comprises a different inversion time between a peak of the inversion recovery pulse and a midpoint of the acquisition of the respective segment of k-space lines, and reconstruction of an image based on the acquired respective segments of k-space lines. In some aspects, the k-space lines acquired by each shot are consecutive in a phase encoding direction of k-space and each shot acquires the segments of k-space lines acquired by prior shots in the sequence, and a time delay between the inversion recovery preparation pulse and acquisition of a first segment for each shot is equal.

Abstract: Described herein is blood flow imaging based on an area under a time-enhancement curve predicted by a computer learning model. Image data comprising a plurality of corresponding images capturing at least a portion of one or both an increase phase and a decline phase of a contrast agent in a cardiovasculature of interest is inputted to a machine learning model to predict an area under a time-enhancement curve of the contrast agent within the cardiovasculature of interest, the predicted area under the time-enhancement curve representing the total sum of contrast agent concentration time product within the cardiovasculature of interest.

Abstract: The disclosure relates to an RF coil device for an MR or hybrid MR-PET imaging modality, the RF coil device having a marker arrangement comprising a plurality of electromagnetic radiation markers disposed at the outer surface of its housing, wherein the electromagnetic radiation markers are adapted to reflect or emit electromagnetic radiation within the ultraviolet, visible, infrared (IR) and/or Terahertz spectrum. The disclosure also relates to detecting the position and/or orientation and/or shape of the RF coil device using electromagnetic radiation emitted from the electromagnetic radiation markers, and determining an attenuation map for the RF coil device by transforming a predefined attenuation map using the determined position and/or orientation and/or shape of the RF coil device.

Abstract: A wireless radio frequency triggered signal acquisition device includes three orthogonal pick up coils in which voltages will be induced by a time varying, spatially varying magnetic field inside a chamber of an MRI scanner. A radio frequency detection circuit detects radio frequency pulses emitted by an MRI scanner and a wireless transmission circuit transmits data from the device. A 3-axis magnetometer is used for measuring magnetic flux in the chamber of the MRI scanner. A processor uses the detected radio frequency pulses to synchronize measurements taken by the magnetometer and pickup coils to a time frame of a gradient driver hardware, thereby matching the measurements to a pulse sequence waveform. The processor further combines measurements of induced voltages in the orthogonal pick up coils and the magnetic flux with the pulse sequence waveform in order to solve for the instantaneous position and orientation of the device.

Abstract: Disclosed herein is a method of operating a medical system (100, 300). The method comprises receiving (200) pulse sequence commands (124) configured to control a magnetic resonance imaging system (302) to acquire k-space data (330) according to a Compressed Sensing magnetic resonance imaging protocol. The method further comprises receiving (202) magnetic resonance scan parameters that are descriptive of a configuration of the pulse sequence commands and a configuration of the magnetic resonance imaging system. The method further comprises receiving (204) an predicted undersampling factor (128) in response to inputting the magnetic resonance scan parameters into a neural network, wherein the neural network is configured to output the predicted undersampling factor in response to receiving magnetic resonance scan parameters. The method further comprises adjusting (206) the pulse sequence commands (130) to select or modify sampling of the k-space data based on the predicted undersampling factor.

Abstract: A surgical guidance system has two cameras to provide stereo image stream of a surgical field; and a stereo viewer. The system has a 3D surface extraction module that generates a first 3D model of the surgical field from the stereo image streams; a registration module for co-registering annotating data with the first 3D model; and a stereo image enhancer for graphically overlaying at least part of the annotating data onto the stereo image stream to form an enhanced stereo image stream for display, where the enhanced stereo stream enhances a surgeon's perception of the surgical field. The registration module has an alignment refiner to adjust registration of the annotating data with the 3D model based upon matching of features within the 3D model and features within the annotating data; and in an embodiment, a deformation modeler to deform the annotating data based upon a determined tissue deformation.

Abstract: An exemplary system, method, and computer-accessible medium for detection of structural disorder(s) of patient(s) can be provided which can include, for example, receiving magnetic resonance imaging (MRI) information of the portion(s), generating gadolinium (“Gd”) enhanced map(s) based on the MRI information using a machine learning procedure(s), and detecting the structural disorder(s) of the patient(s) based on a GD contrast of the Gd enhanced map(s). The Gd enhanced map(s) can be a full dosage Gd enhanced map. The machine learning procedure can be a convolutional neural network. The MRI information can include (i) a low-dosage Gd MRI scan(s), or (ii) a Gd-free MRI scan(s). The Gd contrast can be generated in the Gd enhanced map(s) using a T2-weighted MRI image of the portion(s). Structural disorder(s) can include Stroke, tumor, trauma, infection, Multiple sclerosis and/or other inflammatory disease.

Abstract: An embodiment of the present invention provides a scanning control system for a magnetic resonance imaging system, comprising: a first 3D camera, configured to capture a three-dimensional image of a scan subject located on a scanning table of the magnetic resonance imaging system; a processing device, configured to identify body position information of the scan subject based on the three-dimensional image; and a control device, configured to set scanning parameters related to a body position based on the body position information.

Abstract: A visualization method for evaluating brain addiction traits, an apparatus, and a computer-readable storage medium are provided. The method includes the following. A visualization processing request is received from a client, where the visual processing request contains an image to-be-processed. The image to-be-processed is masked to obtain a perturbation image masked. The perturbation image is classified with a visualization processing model to obtain a classification result, and the classification result is calculated to obtain an evaluation value of the perturbation image, where the evaluation value of the perturbation image is less than an evaluation value of the image to-be-processed without masking. The visualization evaluation result is determined according to the evaluation value of the perturbation image. The visualization evaluation result is sent to the client.

Abstract: Systems and methods are provided for performing operations comprising: generating a radiotherapy treatment plan for treating an ablation volume comprising a myocardial scar based on a first image of a patient that is generated using contrast-enhanced magnetic resonance (MR) imaging information; identifying, based on the first image of the patient, the ablation volume comprising the myocardial scar in a second image of the patient that is generated using MR imaging information without contrast; adjusting the radiotherapy treatment plan based on the ablation volume identified in the second image of the patient; acquiring a cine image of the patient during delivery of a radiotherapy treatment fraction by a radiotherapy treatment device based on the adjusted radiotherapy treatment plan; and comparing the cine image to the second image of the patient to control delivery of a radiotherapy beam by the radiotherapy treatment device.

Abstract: A computer implemented method for dynamic angiographic imaging including: obtaining image data comprising a plurality of corresponding images capturing at least a portion of both an increase phase and a decline phase of a contrast agent in a blood vessel of interest; generating at least one time-enhancement curve of the contrast agent based on the image data; determining a blood flow characteristic in the blood vessel of interest based on the time-enhancement curve. Systems for implementing the method and computer readable media incorporating the method are also described.

Abstract: A system and method for ensuring safe and tolerable insertion of a needle into a subject's body according to a preplanned or continuously monitored sequence of insertion steps. The system comprises a gripping device for gripping the needle in order to perform robotic insertion steps, yet for releasing the grip between such insertion steps, until the next insertion step is initiated. Thereby, the robot has full control of the needle during insertion steps, but does not constrain the needle between insertions, such that movement of the subject can cause neither damage nor discomfort. The gripping and insertion steps may be coordinated to keep in synchronization with the subject's breathing cycles, such that the insertion steps may be performed in the same segment of each cycle of motion of the subject's chest. The gripper can either fully disconnect from the needle, or can partially disconnect but constrain motion within limits.

Abstract: A method of implanting a prosthetic component using bone density information comprises positioning a bone density reference proximate a patient, obtaining two-dimensional x-ray images of a bone of the patient including the bone density reference, determining a density of the bone from the bone density reference in the two-dimensional x-ray images, superimposing the density of the bone into a three-dimensional mean bone model to generate a patient-specific mean bone model, determining an interface between the bone and the prosthetic component based on bone density information of the patient-specific mean bone model, and implanting the prosthetic component in the bone at the interface. Determining the interface comprises evaluating bone density at the interface to place the prosthetic component, determining bone load threshold at the interface to avoid damaging the bone, and determining hardness for the prosthetic implant at the interface to avoid damaging the bone.

Abstract: At least one example embodiment provides a computer-implemented method for evaluating at least one image data set of an imaging region of a patient, wherein at least one evaluation information describing at least one medical condition in an anatomical structure of the imaging region is determined.

Abstract: Objective discrimination of a disease label of a depressive symptom with respect to an active state of a brain is achieved. One means for solving the problems of the present invention is to provide a discriminating device for assisting in determination of whether a subject has a depressive symptom. The discriminating device includes a storage device for storing information for identifying a classifier generated by classifier generation processing based on a signal obtained by using a brain activity detecting apparatus to measure, in advance and time-sequentially, a signal indicating a brain activity of a plurality of predetermined regions of each brain of a plurality of participants in a resting state, the plurality of participants including healthy individuals and patients with depression.

Abstract: A method includes processing at least one input dataset (using a multi-level processing algorithm, one or more of the at least one input dataset comprising imaging data of an echocardiography of a cardiovascular system of a patient. The multi-level processing algorithm comprises a multi-task level and a consolidation-task level. An input of the consolidation-task level is coupled to an output of the multi-task level. The multi-task level is configured to determine multiple diagnostic metrics of the cardiovascular system based on the at least one input dataset. The consolidation-task level is configured to determine a fitness of the cardiovascular system of the patient.

Abstract: An image segmentation method is provided for an electronic device. The method includes pre-training a first initial model based on a plurality of first sample images to obtain a second initial model, the plurality of first sample images including images of a plurality of human tissues, and the second initial model including distribution information of a plurality of target regions corresponding to the plurality of human tissues, training the second initial model based on a plurality of second sample images to obtain an image segmentation model, image information of the plurality of second sample images including at least distribution information of a plurality of target regions corresponding to a target human tissue reflected in the second sample images, and feeding a first image to the image segmentation model, and segmenting, by using the image segmentation model, the first image according to the image information to output a second image.

Abstract: A system and method for producing a series of time-resolved magnetic resonance (MR) images is set forth. The system can perform method steps of encoding spatial information into an MRI signal by manipulating a phase of the MRI signal within an MRI system, generating and outputting a phase-encoded MRI signal over time by digitizing a plurality of time points in the MRI signal, repeating the generating and outputting step for a plurality of phase-encoded signals, each phase-encoded signal in synchrony with a trigger, producing a plurality of digitized time points, and reconstructing a series of time resolved MR images, each image of the series of MR images at one specific time point selected from the plurality of digitized time points for each phase-encoded step. Each image in the series of time-resolved MR images corresponding to a specific time point in a cyclic event.

Abstract: A magnetic resonance imaging apparatus captures a morphology image and a function image that are captured with respect to an equal imaging region of an object under examination. Processing for deforming the morphology image is performed using a deformation parameter and moving positions of structural objects included in the morphology image to respective positions of structural objects of a previously determined standard morphology. Then, the function image is deformed using a value of the deformation parameter used in deforming the morphology image to cause a position of a region included in the function image to coincide with a position of a corresponding region of the standard morphology or by using the standard morphology in an opposite direction using the value of the deformation parameter to cause a position of a region of the structural object thereof to coincide with a position of a corresponding region included in the function image.

Abstract: An imaging method may include obtaining original imaging data of an object in a raw-data domain including original time of flight (TOF) information. The method may also include gating the original imaging data into a plurality of data sets in the raw-data domain. The method may also include determining a plurality of motion vector fields based on the plurality of data sets. The method may also include generating corrected imaging data in the raw-data domain by performing motion correction on at least one of the plurality of data sets based on the original TOF information and at least one corresponding MVF of the plurality of MVFs. The method may also include generating one or more target images of the object by performing, based on the corrected imaging data, image reconstruction.

Abstract: A magnetic resonance imaging (MRI) system and methods for use with a medical, e.g., a surgical, robotic system, involving an MRI apparatus configured to operate with the surgical robotic system, the MRI apparatus having at least one low-field magnet, the at least one low-field magnet configured to generate a low magnetic field, and the low magnetic field comprising a magnetic flux density in a range of approximately 0.1 Tesla (T) to approximately 0.5 T, whereby a standoff between the MRI apparatus and the surgical robotic system is reduced.

Abstract: The present application discloses a system and a device for functional connectivity matrix processing based on feature selection using a filtering method, which comprises the following steps: acquiring a preprocessed resting state brain functional magnetic resonance image of a subject; extracting time series; calculating a Pearson correlation coefficient to obtain a Pearson correlation coefficient matrix; vectorizing the Pearson correlation coefficient matrix; calculating quantitative correlation indices using a filtering method, and selecting a quantitative correlation index based on a preset threshold; performing weighting processing a selected functional connectivity feature by using the corresponding quantitative correlation index with high correlation with a disease diagnosis result to obtain a functional connectivity matrix; and obtaining a prediction result from the functional connectivity matrix.

Abstract: Systems and methods are disclosed for diagnosing and treatment planning for vascular steal syndromes and retrograde flow, One method includes receiving a reference blood flow direction at a location in a reference vasculature; determining a patient-related brood flow direction at a location in a patient's vasculature corresponding to the location in the reference vasculature; determining a difference in direction, between the reference blood flow direction of the reference vasculature and the patient-related blood flow direction of the patient's vasculature; and generating a representation of the location in the patient's vasculature associated with the difference in direction between the reference blood flow direction and the patient-related blood flow direction, or generating a treatment recommendation for the patient's vasculature based on the difference in direction between the reference blood flow direction and the patient-related blood flow direction.

Abstract: In a method for determining a type of characteristic eye movement of the eyes of a patient, the patient is provided with an optokinetic stimulus for the characteristic eye movement, a medical image of the brain of a patient also including the eyes of the patient is generated. An amount of a displacement of an optic nerve of the patient may be determined based on the medical image and a type of a characteristic eye movement may be determined based on the velocity of eye movement for the determined amount of displacement of the optic nerve. In a method for training an artificial intelligence based algorithm for determining an amount of a displacement of an optic nerve of a patient, the algorithm may be trained based on at least one medical image.

Abstract: The present invention relates to a three-dimensional reconstructing method of a 2D medical image. A three-dimensional reconstructing device includes: a communicator for receiving sequential 2D images with an arbitrary slice gap; a sliced image generator for generating at least one sliced image positioned between the 2D images based on a feature point of the adjacent 2D images; and a controller for reconstructing the 2D image into a 3D image by use of the generated sliced image and providing the 3D image.

Abstract: Aspects of generating error-resistant quantum control pulses from geometrical curves are described. In some embodiments, a closed space curve is parameterized for a target gate operation of a quantum computing device. The closed space curve corresponds to an evolution operator of a time-dependent Schrödinger equation associated with the target gate operation. A control field definition is identified for the target gate operation based at least in part on a geometrical analysis of the evolution operator of the time-dependent Schrödinger equation. The target gate operation is implemented for the quantum computing device based on the control field definition.

Abstract: A method of performing magnetic resonance imaging of a body includes a) immerging the body in a static and substantially uniform magnetic field; b) exciting nuclear spins inside the body using at least one radio-frequency pulse; c) applying to the body a time-varying magnetic field gradient defining at least one trajectory (ST) in k-space and simultaneously acquiring samples of a magnetic resonance signal so as to perform a pseudo-random sampling (KS) of the k-space; and d) applying a sparsity-promoting nonlinear reconstruction algorithm for reconstructing a magnetic resonance image of the body; wherein, at least in a low-spatial frequency region of the k-space, the distance between any two adjacent points belonging to a same trajectory is lower than 1/FOV, FOV being the size of a field of view of the reconstructed image. A magnetic resonance imaging apparatus for carrying out such a method is also provided.

Abstract: Described herein is a method of using functional MRI (fMRI) for determining brain activation patterns for a group of subjects in response to different odor-elicited feelings (i.e., conscious emotions). A method for preparing a perfume by using the method of the present invention and a consumer product including said perfume are also described herein.

Abstract: According to one embodiment, MRI apparatus includes processing circuitry and an imaging device. The processing circuitry is configured to acquire at least one of body size information relating to a size of an object and breath-hold information relating to a breath-holdable time of the object. The processing circuitry is further configured to determine an imaging condition to be performed on the object based on the at least one of the body size information and the breath-hold information. The imaging device performs imaging of the object in accordance with the determined imaging condition.

Abstract: A method for performing real-time magnetic resonance (MR) imaging on a subject is disclosed. A prep pulse sequence is applied to the subject to obtain a high-quality special subspace, and a direct linear mapping from k-space training data to subspace coordinates. A live pulse sequence is then applied to the subject. During the live pulse sequence, real-time images are constructed using a fast matrix multiplication procedure on a single instance of the k-space training readout (e.g., a single k-space line or trajectory), which can be acquired at a high temporal rate.

Abstract: Systems and methods provide accelerated MR thermometry utilizing prior knowledge about the images to be reconstructed from incomplete k-space data, thereby facilitating accurate reconstruction. In various embodiments, missing data is computationally estimated using a machine learning algorithm such as a neural network, and an image is generated based on iteratively updated estimated missing information.

Abstract: A method to automatically align magnetic resonance (MR) scans for diagnostic scan planning includes acquiring a three-dimensional (3D) localizer image of an anatomical object. One or more initial landmarks are identified in the 3D localizer image using a landmarking engine. One or more main axes associated with the anatomical object are identified based on the one or more initial landmarks. The 3D localizer image is registered to a canonical space based on the main axes associated to yield a registered 3D localizer image. The landmarking engine is applied to the registered 3D localizer image to yield one or more updated landmarks. A plurality of reference points for performing a MR scan are computed based on the one or more updated landmarks.

Abstract: An imaging system includes a sensor configured to receive imaging data, where the imaging data comprises k-space data from a magnetic resonance imaging (MRI) scan of a patient. The imaging system also includes a processor operatively coupled to the sensor and configured to identify a degree of interaction between measured points of the k-space data located at a radius from a center of k-space. The processor is also configured to determine, based at least in part on the degree of interaction between the measured points, density weights for a density compensation filter. The processor is also configured to apply the density compensation filter to the k-space data to generate filtered k-space data. The processor is further configured to generate an MRI image of the patient based at least in part on the filtered k-space data.

Abstract: One example of a system includes a local user system to interact with an implantable medical device and a local input device communicatively coupled to the local user system to generate local events. To operate the local user system, the local user system is to receive local events from the local input device and remote events from a remote user system communicatively coupled to the local user system via a medical device remote access system. The local user system is to process a local event and ignore a remote event in response to receiving a local event and a remote event simultaneously.

Abstract: A system and method are provided for analysing a functional magnetic resonance imaging (MRI) scan representing a time-sequence, comprising t time points, of images comprising v voxels, where each scan can be represented by a data matrix X?t×v. The method comprises modelling the scan data X as the convolution of neural activation time courses N?+t×v and a haemodynamic filter ?, and performing an inverse operation to estimate N from X and ?. The method further compasses decomposing the neural activation time courses N into multiple brain network components by representing N as the product of a first matrix H defining, for each component, a spatial map of the voxels belonging to that component, and a second matrix W defining, for each component, the time sequence of activation of that component during the scan. In other implementations, the matrix decomposition may be performed before the deconvolution.

Abstract: Systems and methods for neuronavigation in accordance with embodiments of the invention are illustrated. Targeting systems and methods as described herein can generate personalized stimulation targets for the treatment of mental conditions. In many embodiments, direct stimulation of a personalized the stimulation target indirectly impacts a brain structure that is more difficult to reach via the stimulation modality. In various embodiments, the mental condition is major depressive disorder. In a number of embodiments, the mental condition is suicidal ideation.

Abstract: A method of cardiac strain analysis uses displacement encoded magnetic resonance image (MRI) data of a heart of the subject and includes generating a phase image for each frame of the displacement encoded MRI data. Phase images include potentially phase-wrapped measured phase values corresponding to pixels of the frame. A convolutional neural network CNN computes a wrapping label map for the phase image, and the wrapping label map includes a respective number of phase wrap cycles present at each pixel in the phase image. Computing an unwrapped phase image includes adding a respective phase correction to each of the potentially-wrapped measured phase values of the phase image, and the phase correction is based on the number of phase wrap cycles present at each pixel. Computing myocardial strain follows by using the unwrapped phase image for strain analysis of the subject.

Abstract: An embodiment of the present invention provides a scanning control system for a magnetic resonance imaging system, comprising: a first 3D camera, configured to capture a three-dimensional image of a scan subject located on a scanning table of the magnetic resonance imaging system; a processing device, configured to identify body position information of the scan subject based on the three-dimensional image; and a control device, configured to set scanning parameters related to a body position based on the body position information.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining anomalous brain data. One of the methods includes obtaining brain data characterizing brain activity of a patient; for each of a plurality of pairs of parcellations comprising a first parcellation and a second parcellation, processing the brain data to generate a correlation between the brain activity of the first and second parcellations; obtaining second connectivity data that characterizes, for each of the plurality of pairs of parcellations, a normal range of correlations between the brain activity of the first and second parcellations; identifying one or more of the plurality of pairs of parcellations for which the correlation between brain activity of the first and second parcellations is outside of the corresponding normal range of correlations; and providing data characterizing the one or more identified pairs of parcellations for display to a user on a graphical interface.

Abstract: A method and system for reducing or removing motion artefacts in magnetic resonance (MR) images, the method including the steps of: receiving a motion corrupted MR image; determining a corrected intensity value for each pixel in the motion corrupted MR image by using a neural network; and generating a motion corrected MR image based on the determined corrected intensity values for the pixels in the motion corrupted MR image.

Abstract: In a method and apparatus for acquiring and reconstructing a four-dimensional dynamic magnetic resonance (MR) image data record, MR data are continuously acquired by radial scanning of an examination region along radial k-space lines, and a dynamic region of the examination region, in which said dynamic procedure is relevant, is determined, as well as a non-dynamic region, which is not relevant to the dynamic procedure. Static image data are reconstructed from all of the acquired MR data, and image data therein originating from the non-dynamic region are marked and are then not used for reconstructing a dynamic image data record for the dynamic region.

Abstract: A method of generating a quantitative characterization of injury presence and status of spinal cord tissue using an adaptive CNN system for use in diagnostic assessment, surgical planning, and therapeutic strategy comprises preprocessing for artifact correction of diffusion based, spinal cord MRI data, training an adaptive CNN system with healthy and abnormal (injured/pathologic) spinal cord images obtained by imaging a population of healthy, typically developed spinal cord subjects and subjects with spinal cord injury, evaluating a novel, diffusion-based MRI image for injury biomarkers using the adaptive CNN system, generating a three-dimensional predictive axonal damage map for quantitative characterization and visualization of the novel, diffusion-based MRI image, and transmitting the sets of healthy and injured spinal cord images back to a central database for continued improvement of the adaptive CNN system training. A system for defining a predictive spinal axonal damage map is also described.

Abstract: A method for ascertaining at least one of a position or an orientation of an MR local coil unit for arrangement inside a main magnetic field includes providing a first 3D relative position of a reference sensor system in relation to the main magnetic field; receiving an acceleration vector from at least one acceleration sensor; retrieving a distance vector describing a fixed relative position as a function of the received acceleration vector; calculating a second 3D relative position of the at least one acceleration sensor in relation to the main magnetic field based on the first 3D relative position and the retrieved distance vector; and ascertaining the at least one of the position or the orientation of the MR local coil unit using the first 3D relative position and the second 3D relative position.

Abstract: Described herein is medical imaging technology for concurrent and simultaneous synthesis of a medical CA-free-AI-enhanced image and medical diagnostic image analysis comprising: receiving a medical image acquired by a medical scanner in absence of contrast agent enhancement; providing the medical image to a computer-implemented machine learning model; concurrently performing a medical CA-free-AI-enhanced image synthesis task and a medical diagnostic image analysis task with the machine learning model; reciprocally communicating between the image synthesis task and the image analysis task for mutually dependent training of both tasks. Methods and systems and non-transitory computer readable media are described for execution of concurrent and simultaneous synthesis of a medical CA-free-AI-enhanced image and medical diagnostic image analysis.

Abstract: According to one embodiment, a magnetic resonance imaging apparatus includes sequence control circuitry and processing circuitry. The sequence control circuitry performs under-sampled data acquisition whose sample points are located at an equal interval in k-space and acquires k-space frames. The processing circuitry generates a plurality of k-space frames related to a plurality of time resolutions based on the k-space frames. In each of the plurality of k-space frames, the sample points are located at an equal interval, and the interval differs for each of the plurality of k-space frames. The processing circuitry generates a time-series image based on the plurality of k-space frames.

Abstract: A computer-implemented method for generating an artifact corrected reconstructed contrast image from magnetic resonance imaging (MRI) data is provided. The method includes inputting into a trained deep neural network both a synthesized contrast image derived from multi-delay multi-echo (MDME) scan data or the MDME scan data acquired during a first scan of an object of interest utilizing a MDME sequence and a composite image, wherein the composite image is derived from both the MDME scan data and contrast scan data acquired during a second scan of the object of interest utilizing a contrast MRI sequence. The method also includes utilizing the trained deep neural network to generate the artifact corrected reconstructed contrast image based on both the synthesized contrast image or the MDME scan data and the composite image. The method further includes outputting from the trained deep neural network the artifact corrected reconstructed contrast image.

Abstract: A head stabilization device or HFD includes a plurality of integrated markers. The HFD may be in the form of a skull clamp, vacuum bag, combinations thereof, or other supporting structure. The integrated markers include MRI markers detectable by an MRI scanner and fiducial markers detectable by a registration tool of a navigation system. The markers provide a reference point relative to an operation site in a patient for use in a navigation guided procedure and aid in registering or calibrating the location of the patient with captured images used in the navigation guided procedure.

Abstract: A method for medical imaging may include determining a posture of an object and obtaining a first parameter of a pulse sequence to be applied to the object. The method may also include determining, based on the posture and the first parameter, a SAR distribution model and estimating, based on the SAR distribution model and a second parameter of the pulse sequence to be applied, a SAR distribution associated with the object under the pulse sequence to be applied. The second parameter is associated with calibration of the pulse sequence to be applied. The method may further include determining whether the estimated SAR distribution meets a condition and causing, in response to a result of the determination that the estimated SAR distribution associated with the object meets the condition, a scanner to perform an MR scan on the object according to the pulse sequence.