Abstract: A system may measure, using a measurement device, a response associated with a sample to an excitation. Then, the system may compute, using the measured response and the excitation as inputs to one of an inverse model and a predetermined predictive model, model parameters on a voxel-by-voxel basis in a forward model with multiple voxels that represent the sample. The forward model may simulate response physics occurring within the sample to a given excitation, and the model parameters may include magnetic susceptibilities of the multiple voxels. Moreover, the system may determine an accuracy of the model parameters by comparing at least the measured response and a calculated predicted value of the response using the forward model, the model parameters and the excitation. When the accuracy exceeds a predefined value, the system may provide the model parameters as an output to: a user, another electronic device, a display, and/or a memory.

Abstract: A system may measure, using a measurement device, a response associated with a sample to an excitation. Then, the system may compute, using the measured response and the excitation as inputs to one of an inverse model and a predetermined predictive model, model parameters on a voxel-by-voxel basis in a forward model with multiple voxels that represent the sample. The forward model may simulate response physics occurring within the sample to a given excitation, and the model parameters may include magnetic susceptibilities of the multiple voxels. Moreover, the system may determine an accuracy of the model parameters by comparing at least the measured response and a calculated predicted value of the response using the forward model, the model parameters and the excitation. When the accuracy exceeds a predefined value, the system may provide the model parameters as an output to: a user, another electronic device, a display, and/or a memory.

Abstract: A system may measure, using a measurement device, a response associated with a sample to an excitation. Then, the system may compute, using the measured response and the excitation as inputs to a predetermined predictive model, model parameters on a voxel-by-voxel basis in a forward model with multiple voxels that represent the sample. The forward model may simulate response physics occurring within the sample to a given excitation. For example, the forward model may be based on differential or phenomenological equations that approximates the response physics. Moreover, the system may determine an accuracy of the model parameters by comparing at least the measured response and a calculated predicted value of the response using the forward model, the model parameters and the excitation. When the accuracy exceeds a predefined value, the system may provide the model parameters as an output to: a user, another electronic device, a display, and/or a memory.

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 system performs one or more magnetic resonance (MR) measurements on at least a portion of a biological life form. Moreover, the system quantitatively simulates an MR response of at least the portion of the biological life form, and compares the one or more MR measurements and the quantitative simulation to obtain a first test result. Next, the system determines one or more additional medical tests to perform. In response, the system accesses the biological sample in storage, and performs the one or more additional medical tests on at least a second portion of the biological sample to obtain one or more additional test results. Furthermore, the system computes a second test result based at least in part on the first test result and the one or more additional test results, where the second test result has an improved accuracy relative to the first test result.

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: A system that iteratively performs medical testing is described. During operation, the system receives a test result of a medical test performed on a biological sample associated with an individual, where the test result has an initial uncertainty. Then, the system determines, based on the test result, a second medical test to perform on a second biological sample associated with the individual, where the second biological sample was acquired prior to the biological sample. Moreover, the system performs the second medical test on the second biological sample to obtain a second test result of the second medical test. Next, the system computes a revised result for the medical test based on the test result and the second test result, where the revised result has a second uncertainty that is less than the initial uncertainty.

Abstract: During operation, a system may apply a polarizing field and an excitation sequence to a sample. Then, the system may measure a signal associated with the sample for a time duration that is less than a magnitude of a relaxation time associated with the sample. Next, the system may calculate the relaxation time based on a difference between the measured signal and a predicted signal of the sample, where the predicted signal is based on a forward model, the polarizing field and the excitation sequence. After modifying at least one of the polarizing field and the excitation sequence, the aforementioned operations may be repeated until a magnitude of the difference is less than a convergence criterion. Note that the calculations may be performed concurrently with the measurements and may not involve performing a Fourier transform on the measured signal.

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 computer system may perform substitutions for fields in a set of records, where performing a given substitution involves replacing a field in the set of records with a replacement field, and the substitutions remove the context information in the set of records while maintaining relevance of the set of records. Then, the computer system may generate an artificial set of records based, at least in part, on the set of records, where a given artificial record includes one or more modified portions of the set of records. Next, the computer system may combine the set of records and the artificial set of records into a second set of records, where at least some phrases or values in the second set of records are uniformly distributed.

Abstract: A computer system may iteratively modify a local medical rule that is based on an initial sub-population. In particular, after information specifying the local medical rule and sharing instructions are received from a user of the computer system, the computer system may iteratively apply the local medical rule to one or more additional sub-populations that are associated with other users of the computer system based on the sharing instructions without sharing PHI associated with the initial sub-population. Then, the computer system may aggregate results for the one or more additional sub-populations, and may generate the population-based medical rule by modifying the local medical rule based on the aggregated results and one or more quality metrics. Moreover, the computer system may selectively provide the population-based medical rule to the user without sharing PHI associated with the one or more additional sub-populations.

Abstract: A computer system may perform substitutions for fields in a set of records, where performing a given substitution involves replacing a field in the set of records with a replacement field, and the substitutions remove the context information in the set of records while maintaining relevance of the set of records. Then, the computer system may generate an artificial set of records based, at least in part, on the set of records, where a given artificial record includes one or more modified portions of the set of records. Next, the computer system may combine the set of records and the artificial set of records into a second set of records, where at least some phrases or values in the second set of records are uniformly distributed.