# US 12,213,837 B2 · Apparatus and method

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- Number: US 12,213,837 B2
- Document ID: US12213837B2
- Status: Granted
- Kind: B2
- Application number: 18/609,670
- Filed: 2024-03-19
- Published: 2024-07-04
- Granted: 2025-02-04
- Earliest claimed: 2020-04-06
- Assignees: Canon Medical Systems Corporation
- Applicants: Canon Medical Systems Corporation
- Inventors: Kousuke Namiki
- Web page: https://patentgrep.com/patent/US12213837B2

## CPC

- A61B 8/0891: {for diagnosis of blood vessels}
- A61B 8/5223: {for extracting a diagnostic or physiological parameter from medical diagnostic data (for algorithms to analyse biomedical images G06T7/0012)}
- A61B 8/065: {to determine blood output from the heart}
- A61B 8/0883: {for diagnosis of the heart}
- A61B 8/463: {characterised by displaying multiple images or images and diagnostic data on one display}
- A61B 8/488: {involving Doppler signals}
- A61B 8/5207: {involving processing of raw data to produce diagnostic data, e.g. for generating an image}
- A61B 8/5269: {involving detection or reduction of artifacts}
- A61B 8/5284: {involving retrospective matching to a physiological signal}
- G06T 7/70: Determining position or orientation of objects or cameras (camera calibration G06T7/80)
- G16H 30/20: for handling medical images, e.g. DICOM, HL7 or PACS
- G16H 30/40: for processing medical images, e.g. editing
- G16H 40/63: for local operation
- G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems
- G16H 50/70: for mining of medical data, e.g. analysing previous cases of other patients
- G06T 2207/10132: Ultrasound image
- G06T 2207/20081: Training; Learning
- G06T 2207/30048: Heart; Cardiac
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

An apparatus according to an embodiment includes a processing circuit. The processing circuit is configured to obtain first Doppler waveform data related to a left ventricular blood inflow. The processing circuit is configured to detect positions of an E-wave and an A-wave in the first Doppler waveform data, by using the first Doppler waveform data and a trained model trained with training data that includes at least positions of an E-wave and an A-wave in each of a plurality of pieces of second Doppler waveform data related to left ventricular blood inflows and the plurality of pieces of second Doppler waveform data.

## Claims

### Claim 1

An apparatus, comprising:
processing circuitry configured to
obtain first ultrasound data related to a left ventricular blood inflow; and
obtain information corresponding to waveforms of Early Wave (E-wave) and Atrium Wave (A-wave) included in the first ultrasound data based on the obtained first ultrasound data and a trained model trained with training data that includes second ultrasound data related to a left ventricular blood inflow and waveforms of an E-wave and an A-wave included in the second ultrasound data,
wherein the first ultrasound data includes any of noise equal to or higher than a reference value, aliasing, or brightness equal to or lower than a reference value, and the information is obtained from the first ultrasound data by using the trained model.

### Claim 2 (depends on 1)

The apparatus according to claim 1, wherein the first ultrasound data includes Doppler waveform data containing at least noise equal to or higher than the reference value.

### Claim 3 (depends on 1)

The apparatus according to claim 1, wherein the first ultrasound data includes Doppler waveform data containing aliasing.

### Claim 4 (depends on 1)

The apparatus according to claim 1, wherein
the first ultrasound data is Doppler waveform data including a Doppler waveform corresponding to at least one heartbeat, and
the processing circuitry is further configured to display guide information indicating positions of the E-wave and the A-wave included in the first ultrasound data on a Doppler waveform image that is represented by the Doppler waveform data.

### Claim 5 (depends on 1)

The apparatus according to claim 1, wherein
the first ultrasound data is Doppler waveform data including a Doppler waveform corresponding to at least one heartbeat, and
the processing circuitry is further configured to obtain an electrocardiogram (ECG) waveform synchronized with the Doppler waveform data, and display the ECG waveform and a Doppler waveform image that is represented by the Doppler waveform data, side by side.

### Claim 6 (depends on 1)

The apparatus according to claim 1, wherein
the information includes an E-wave flow velocity value, an A-wave flow velocity value, a ratio between the E-wave flow velocity value and the A-wave flow velocity value, and deceleration time of the E-wave, and
the processing circuitry is further configured to display at least one of the E-wave flow velocity value, the A-wave flow velocity value, the ratio between the E-wave flow velocity value and the A-wave flow velocity value, and the deceleration time of the E-wave.

### Claim 7 (depends on 1)

The apparatus according to claim 1, wherein
the processing circuitry is further configured to obtain the information in response to a freeze operation.

### Claim 8 (depends on 1)

The apparatus according to claim 1, wherein
the processing circuitry is further configured to obtain the information in response to an instruction to execute a detecting process.

### Claim 9

A method, comprising:
obtaining first ultrasound data related to a left ventricular blood inflow; and
obtaining information corresponding to waveforms of Early Wave (E-wave) and Atrium Wave (A-wave) included in the first ultrasound data based on the obtained first ultrasound data and a trained model trained with training data that includes second ultrasound data related to a left ventricular blood inflow and waveforms of an E-wave and an A-wave included in the second ultrasound data,
wherein the first ultrasound data includes any of noise equal to or higher than a reference value, aliasing, or brightness equal to or lower than a reference value, and the information is obtained from the first ultrasound data by using the trained model.