Medical information processing apparatus and medical information processing method
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.
1. A medical information processing apparatus comprising a processing circuitry,
the processing circuitry being configured to
acquire medical data on a subject,
acquire digital data which represents an acquisition condition of the medical data, the acquisition condition being set before acquisition of the medical data, and
apply a machine learning model to input data including the digital data and the medical data to generate output data based on the medical data, wherein
the digital data includes a plurality of elements corresponding to a plurality of candidates of the acquisition condition, and
each of the elements includes a value according to whether a corresponding candidate is accepted and/or a content of the corresponding candidate.
2. The medical information processing apparatus according to claim 1 , wherein the machine learning model receives inputs of the digital data and the medical data and learns using teacher data.
3. The medical information processing apparatus according to claim 1 , wherein the value of the element has one of a first value indicating that the acquisition condition is adopted and a second value indicating that the acquisition condition is not adopted.
4. The medical information processing apparatus according to claim 1 , wherein
the digital data includes an element having two or more finite number of elements, and
the elements by the number of the elements include a first element corresponding to the candidate conditions and a second element corresponding to none of the candidates.
5. The medical information processing apparatus according to claim 1 , wherein the acquisition condition includes a type of pulse sequence, a frame number, a type of k-space filling trajectory, a number of times of repetition of repetition operation and/or an acceleration factor of parallel imaging.
6. The medical information processing apparatus according to claim 1 , wherein the processing circuitry generates data to be provided for medical diagnosis on the subject as the output data.
7. The medical information processing apparatus according to claim 1 , wherein the machine learning model is configured to multiply each of the digital data and the medical data by weight different and add a product for each channel.
8. The medical information processing apparatus according to claim 1 , wherein
the processing circuitry is configured to
acquire the digital data obtained by digitizing the acquisition condition of medical imaging for the subject,
acquire raw data acquired by the medical imaging according to the acquisition condition as the medical data, and
apply the machine learning model to input data including the digital data and the raw data or a medical image based on the raw data to generate the output data based on the raw data or the medical image.
9. The medical information processing apparatus according to claim 8 , wherein the processing circuit performs reconstruction processing on the input data including the digital data and the raw data using a machine learning model to generate the image data on the subject.
10. The medical information processing apparatus according to claim 8 , wherein
the acquisition condition is a number of times of acquisition and/or a direction of acquisition for each data acquisition trajectory, and
the digital data is mask data in which a numerical value corresponding to the number of times of acquisition and/or the direction of acquisition in target imaging is assigned to a plurality of data acquisition trajectory candidates having a finite number of elements.
11. The medical information processing apparatus according to claim 10 , wherein the processing circuitry determines the number of times of acquisition and/or the direction of acquisition for the data acquisition trajectory candidates according to a user's instruction or automatically.
12. The medical information processing apparatus according to claim 10 , wherein the processing circuitry determines the number of times of acquisition and/or the direction of acquisition for the data acquisition trajectory candidates according to a predetermined rule based on an imaging time in the medical imaging.
13. The medical information processing apparatus according to claim 10 , wherein the digital value includes a first numerical value indicating that data acquisition is to be performed and a second numerical value indicating that data acquisition is not to be performed.
14. The medical information processing apparatus according to claim 10 , wherein each of the data acquisition trajectory candidates is a data acquisition trajectory in k-space related to the radial method, and linearly passes substantially a center of the k-space.
15. The medical information processing apparatus according to claim 14 , wherein an angular interval between the data acquisition trajectory candidates is set to a predetermined angle.
16. The medical information processing apparatus according to claim 14 , wherein the data acquisition trajectory candidates are arranged at substantially equal intervals at an angle based on an angle obtained by dividing 360 degrees by the number of the elements.
17. The medical information processing apparatus according to claim 10 , wherein each of the data acquisition trajectory candidates is a data acquisition trajectory in k-space related to a spiral method, and spirally passes through the k-space.
18. The medical information processing apparatus according to claim 10 , wherein the processing circuitry applies the machine learning model to the mask data and the raw data, generates de-noised raw data as the output data, and performs Fourier transformation on the de-noised raw data to generate the medical image.
19. The medical information processing apparatus according to claim 18 , wherein the processing circuitry performs Fourier transformation on the raw data to generate a provisional medical image, applies the machine learning model to the mask data and the provisional medical image, and outputs the de-noised medical image as the output data.
20. The medical information processing apparatus according to claim 1 , further comprising an imaging apparatus configured to perform magnetic resonance imaging on the subject and acquire k-space data as the medical data.
21. A medical information processing method comprising:
acquiring medical data related to a subject;
acquiring digital data which represents an acquisition condition for the medical data, the acquisition condition being set before acquisition of the medical data; and
applying a machine learning model to input data including the digital data and the medical data to generate output data based on the medical data, wherein
the digital data includes a plurality of elements corresponding to a plurality of candidates of the acquisition condition, and
each of the elements includes a value according to whether a corresponding candidate is accepted and/or a content of the corresponding candidate.