Abstract: A system for MR Elastography of a sample, including ultrasound gel to sheath the sample, a vessel to accept the flow of the sample sheathed in ultrasound gel, a sensor array adapted to capture an ultrasound measurement and an MR measurement, wherein the sensor array including an ultrasound transmitter and an ultrasound receiver, and the sensor array is coupled to the vessel, and the vessel is capable of mechanical conductance between the ultrasound transducers, and the ultrasound gel, and a pump to create a pressure based flow of ultrasound fluid through the vessel and move the sample in proximity to the sensor array for capture of MR and ultrasound measurements of the sample as the sheathed sample passes by the sensor array.

Abstract: An apparatus for use in a magnetic resonance (MR) system for capturing an MR Elastography measurement of a biological lifeform may include a platform; a gel pad on a surface of the platform; and a sensor array. In some embodiments, the sensor array includes at least one ultrasound transducer, and at least one radiofrequency (RF) transmitter and receiver coil. The sensor array is at least partially embedded within the gel pad, and the gel pad is configured to provide mechanical impedance matching between the at least one ultrasound transducer and the biological lifeform. In some embodiments, a system includes the apparatus and an MR system, the MR system including an ultrasonic wave generator, an interface circuit, and a computing device. In some such embodiments, the ultrasonic wave generator is configured to generate one or more shear waves in the biological lifeform.

Abstract: During operation, a system may obtain first and second magnetic resonance (MR) measurements associated with a biological lifeform, where the first and second MR measurements were acquired while the biological lifeform engaged in free breathing and/or without prospective gating based on a cardiac rhythm of the biological lifeform, and the first and second MR measurements were acquired at different times. Then, the system may dynamically determine first and second instances of one or more anatomical structures associated with the biological lifeform based at least in part on the first and second MR measurements, and a segmentation technique. Next, the system may perform a quantitative comparison of the first instance of the one or more anatomical structures and the second instance of the one or more anatomical structures, where the quantitative comparison has an uncertainty of less than a predefined value.

Abstract: A computer system that performs a sparsity technique is described. During operation, the computer system accesses or obtains information associated with non-invasive measurements performed on at least an individual, historical non-invasive measurements, and a dictionary of predetermined features or basis functions associated with the historical non-invasive measurements. Note that the non-invasive measurements and the historical non-invasive measurements may include or correspond to magnetic resonance (MR) measurements. For example, the MR measurements may include magnetic resonance imaging (MRI) scans. Then, the computer system updates the dictionary of predetermined features based at least in part on the non-invasive measurements and the historical non-invasive measurements, where the updating includes performing a minimization technique with a cost function having an L2-norm term and an L0-norm term.

Abstract: A computer system that performs a sparsity technique is described. During operation, the computer system accesses or obtains information associated with non-invasive measurements performed on at least an individual, historical non-invasive measurements, and a dictionary of predetermined features or basis functions associated with the historical non-invasive measurements. Note that the non-invasive measurements and the historical non-invasive measurements may include or correspond to magnetic resonance (MR) measurements. For example, the MR measurements may include magnetic resonance imaging (MRI) scans. Then, the computer system updates the dictionary of predetermined features based at least in part on the non-invasive measurements and the historical non-invasive measurements, where the updating includes performing a minimization technique with a cost function having an L2-norm term and an L0-norm term.

Abstract: During operation, a system may apply an external magnetic field and an RF pulse sequence to a sample. Then, the system may measure at least a component of a magnetization associated with the sample, such as MR signals of one or more types of nuclei in the sample. Moreover, the system may calculate at least a predicted component of the magnetization for voxels associated with the sample based on the measured component of the magnetization, a forward model, the external magnetic field and the RF pulse sequence. Next, the system may solve an inverse problem by, iteratively modifying the parameters associated with the voxels in the forward model until a difference between the predicted component of the magnetization and the measured component of the magnetization is less than a predefined value. Note that the calculations may be performed concurrently with the measurements and may not involve performing a Fourier transform.

Abstract: During operation, a system may apply an external magnetic field and an RF pulse sequence to a sample. Then, the system may measure at least a component of a magnetization associated with the sample, such as MR signals of one or more types of nuclei in the sample. Moreover, the system may calculate at least a predicted component of the magnetization for voxels associated with the sample based on the measured component of the magnetization, a forward model, the external magnetic field and the RF pulse sequence. Next, the system may solve an inverse problem by iteratively modifying the parameters associated with the voxels in the forward model until a difference between the predicted component of the magnetization and the measured component of the magnetization is less than a predefined value. Note that the calculations may be performed concurrently with the measurements and may not involve performing a Fourier transform.

Abstract: During operation, a system may apply an external magnetic field and an RF pulse sequence to a sample. Then, the system may measure at least a component of a magnetization associated with the sample, such as MR signals of one or more types of nuclei in the sample. Moreover, the system may calculate at least a predicted component of the magnetization for voxels associated with the sample based on the measured component of the magnetization, a forward model, the external magnetic field and the RF pulse sequence. Next, the system may solve an inverse problem by iteratively modifying the parameters associated with the voxels in the forward model until a difference between the predicted component of the magnetization and the measured component of the magnetization is less than a predefined value. Note that the calculations may be performed concurrently with the measurements and may not involve performing a Fourier transform.

Abstract: A user interface for medical information includes a timeline that can be highlighted or selected by a time window with a time duration, and the information plots of biomarkers displayed in subsystem displays can update to display the biomarker information for the time duration highlighted by the time window. The trendline, baseline, and data points shown on the information plot(s) can also be adjusted to display only information during the time duration highlighted or selected by the time window.

Abstract: During operation, a system may apply an external magnetic field and an RF pulse sequence to a sample. Then, the system may measure at least a component of a magnetization associated with the sample, such as MR signals of one or more types of nuclei in the sample. Moreover, the system may calculate at least a predicted component of the magnetization for voxels associated with the sample based on the measured component of the magnetization, a forward model, the external magnetic field and the RF pulse sequence. Next, the system may solve an inverse problem by iteratively modifying the parameters associated with the voxels in the forward model until a difference between the predicted component of the magnetization and the measured component of the magnetization is less than a predefined value. Note that the calculations may be performed concurrently with the measurements and may not involve performing a Fourier transform.

Abstract: An apparatus for use in a magnetic resonance (MR) system for capturing an MR Elastography measurement of a biological lifeform may include a platform; a gel pad on a surface of the platform; and a sensor array. In some embodiments, the sensor array includes at least one ultrasound transducer, and at least one radiofrequency (RF) transmitter and receiver coil. The sensor array is at least partially embedded within the gel pad, and the gel pad is configured to provide mechanical impedance matching between the at least one ultrasound transducer and the biological lifeform. In some embodiments, a system includes the apparatus and an MR system, the MR system including an ultrasonic wave generator, an interface circuit, and a computing device. In some such embodiments, the ultrasonic wave generator is configured to generate one or more shear waves in the biological lifeform.

Abstract: A user interface for medical information includes a timeline that can be highlighted or selected by a time window with a time duration, and the information plots of biomarkers displayed in subsystem displays can update to display the biomarker information for the time duration highlighted by the time window. The trendline, baseline, and data points shown on the information plot(s) can also be adjusted to display only information during the time duration highlighted or selected by the time window.