Abstract: According to one embodiment, a medical information processing apparatus comprising processing circuitry. The processing circuitry acquires first medical data having a first data resolution and second medical data having a second data resolution. The processing circuitry acquires an acquisition condition for medical data relating to at least one of the first medical data and the second medical data. The processing circuitry outputs a result integrated at least a piece of information that is based on the first medical data and the second medical data by inputting the first medical data, the second medical data and the acquisition condition to a trained model.

Abstract: According to one embodiment, a medical information processing apparatus comprising processing circuitry. The processing circuitry performs, on each of a plurality of resolution data items, one or more times of first noise reduction processing of reducing noise and one or more times of first DC processing of enhancing a data consistency, and generate output data items corresponding the resolution data items. when processing the second and subsequent resolution data items, The processing circuitry performs one or more times of second noise reduction processing and one or more times of second DC processing on a target resolution data item and one or more output data items generated before the target resolution data item, and generates a newly output data item.

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 medical data processing device according to an embodiment includes a processing circuit. The processing circuit applies a linear calculation of a complex number coefficient and a non-linear activation not dependent on an argument of complex numbers, to medical data having a complex value.

Abstract: An apparatus of machine learning includes processing circuitry. The processing circuitry uses a first calibration model that receives, as input, first processing data and a first processing label assigned by a user to the first processing data and outputs calibration data relating to calibration of individual characteristics in label assignment by the first user, and trains a target model based on at least the first processing data and the calibration data or a calibrated label having individual characteristics calibrated using the calibration data.

Abstract: According to one embodiment, a medical information processing apparatus has processing circuitry. The processing circuitry acquires medical data on a subject, acquires numerical data obtained by digitizing an acquisition condition of the medical data, and applies a machine learning model to input data including the numerical data and the medical data, thereby generating output data based on the medical data.

Abstract: A data processing device according to an embodiment includes a processing circuit. The processing circuit includes a complex number neural network with an activation function by which an output varies according to an argument of complex.

Abstract: According to one embodiment, a reconstruction apparatus obtains acquired raw data, and reconstruct a data set that represents a measured physical amount with a multidimensional space based on the acquired raw data. Herein, the apparatus performs reduction processing for generating noise-reduced partial data from partial data relating to a partial area of a data set at a current number of iterations, error compensation processing for compensating errors in a data set at the current number of iterations with respect to the acquired raw data, and optimization processing for reconstructing the data set by repeating the reduction processing and the error compensation processing until predetermined criteria are met, while moving the partial area.

Abstract: According to one embodiment, a pseudo data generation apparatus comprising processing circuitry. The processing circuitry collects a data set including data values of one or more dimensions. The processing circuitry performs conversion of the data values of the one or more dimensions included in the data set. The processing circuitry generates a pseudo physical parameter relating to each of one or more physical amounts.

Abstract: According to one embodiment, a medical image processing apparatus includes an acquirer, a first processor and a second processor. The acquirer is configured to acquire nonequispaced sampled data from a test object. The first processor is configured to derive product-sums of the nonequispaced sampled data acquired by the acquirer and a plurality of coefficient sets and generate equispaced sampled data including a plurality of elements with which the product-sums derived for the coefficient sets are associated as element values. The second processor is configured to generate a medical image in which at least part of the test object has been imaged through reconstruction basis on the equispaced sampled data generated by the first processor.

Abstract: According to one embodiment, a data compression apparatus includes processing circuitry. The processing circuitry generates reconstructed data by performing reconstruction processing on data. The processing circuitry generates decompressed reconstructed data by performing the reconstruction processing on decompressed data obtained by decompressing compressed data that is generated by performing compression processing on the data. The processing circuitry determines a parameter relating to a compression ratio of the data based on comparison between the reconstructed data and the decompressed reconstructed data.

Abstract: A signal processing apparatus according to the present embodiment computes a first integral value corresponding to an element in a coefficient sequence of a first input sequence and a second integral value corresponding to the element in a coefficient sequence of a second input sequence next to the first input sequence, and includes a processing circuitry. The processing circuitry adds a value not overlapping the first input sequence in the second input sequence to the first integral value and subtracts a value not overlapping the second input sequence in the first input sequence from the first integral value for the element, thereby computing the second integral value.

Abstract: A medical data processing apparatus includes a memory and processing circuitry. The memory stores a learned model including an input layer to which first MR data and second MR data having the same imaging target as the first MR data and an imaging parameter different from the first MR data are inputted, an output layer from which third MR data is output with a missing portion of the first MR data restored, and at least one intermediate layer arranged between the input layer and the output layer. The processing circuitry generates third MR data relating to the subject, from the first MR data serving as a process target and relating to the subject and the second MR data relating to the subject and acquired by an imaging parameter different from the first MR data serving as the process target, in accordance with the learned model.

Abstract: According to one embodiment, a data processing apparatus includes processing circuitry. The processing circuitry acquires input data relating to a processing target including a plurality of data segments corresponding respectively to a plurality of imaging contrasts determined by a first pulse sequence. The processing circuitry generates output data relating to the processing target by applying a trained model to input data relating to the processing target. The processing circuitry outputs output data relating to the processing target.

Abstract: According to one embodiment, a data compression apparatus includes processing circuitry. The processing circuitry generates reconstructed data by performing reconstruction processing on data. The processing circuitry generates decompressed reconstructed data by performing the reconstruction processing on decompressed data obtained by decompressing compressed data that is generated by performing compression processing on the data. The processing circuitry determines a parameter relating to a compression ratio of the data based on comparison between the reconstructed data and the decompressed reconstructed data.

Abstract: An image generating apparatus according to the embodiment includes processing circuitry. The processing circuitry acquires MR data acquired in read-out directions including a first read-out direction and a second read-out direction intersecting the first read-out direction, filter sensitivity distributions corresponding to the read-out directions and indicating distributions of sensitivity of a low-pass filter, and coil sensitivity distributions corresponding to coil elements used to acquire the MR data. The processing circuitry generates synthesis sensitivity distributions for the respective read-out directions by synthesizing the filter sensitivity distributions and the coil sensitivity distributions for the respective read-out directions. The processing circuitry generates an MR image based on the synthesis sensitivity distributions and MR data.

Abstract: An MRI apparatus according to the present embodiment acquires a plurality of MR signals corresponding to read-out directions including a first read-out direction and a second read-out direction intersecting the first read-out direction, and. The MRI apparatus includes processing circuitry and a low-pass filter. The processing circuitry specifies a signal area relating to generation of the MR signals in a subject. The processing circuitry sets a cutoff frequency defining a passband for the MR signals based on the signal area. The low-pass filter filters the MR signals acquired by scanning performed on the subject in the read-out directions using the cutoff frequency. The processing circuitry generates an MR image based on MR data generated by A/D conversion performed on the MR signals output from the low-pass filter.

Abstract: According to one embodiment, an information processing apparatus includes processing circuitry. The processing circuitry calculates a plurality of bases by performing a basis conversion on signal data. The processing circuitry selects one or more specific bases with contribution rates lower than a reference from among the bases. The processing circuitry executes data processing utilizing the specific bases.

Abstract: A photon counting X-ray CT apparatus according to an embodiment includes: data acquiring circuitry, and processing circuitry. The data acquiring circuitry is configured to allocate energy measured by signals output from a photon counting detector in response to incidence of X-ray photons to any of a plurality of first energy bins so as to acquire a first data group as count data of each of the first energy bins. The processing circuitry is configured to determine a plurality of second energy bins obtained by grouping the first energy bins in accordance with a decomposition target material that is a material to be decomposed in a imaging region, allocate the first data group to any of the second energy bins so as to generate a second data group, and use the second data group to generate an image representing a distribution of the decomposition target material.

Abstract: According to one embodiment, medical signal processing apparatus includes a processing circuit. The processing circuit adjust a level of activation of a unit included in a learned model in accordance with classification of an imaging condition for a process target medical signal. The processing circuit generates an output signal by applying the learned model in which the level of activation has been adjusted, to the medical signal.