Abstract: A detection unit detects a lesion candidate contained in display frame data (a tomographic image), using a machine learned detection model. An exclusion processing unit collates a feature vector of the detected lesion candidate with feature vectors registered in an exclusion database to determine whether the detected lesion candidate is an exclusion target. When the detected lesion candidate is an exclusion target, a mark display control unit restricts display of a mark for indicating a lesion candidate.

Abstract: An evaluation unit evaluates performance of an analytic model (internal analytic model) based on internal data extracted from the analytic model and output data of the analytic model. A determination unit determines use of an external analytic model based on an evaluation result of the evaluation unit. In that case, an input image (tomographic image) is sent to an information processing apparatus via a communication unit. An analysis result of the analytic model (external analytic model) is sent to a calculation control unit via the communication unit.

Abstract: A log management unit creates a log in which an operation of an ultrasound diagnostic apparatus is recorded. A model operation management unit saves an analysis target image input to an image analysis model and an analysis result of the image analysis model for each operation of the image analysis model. In a case where a specific model operation record in the log is selected, the report creation unit creates a model operation report. The model operation report includes the analysis target image input to the image analysis model and the analysis result of the image analysis model.

Abstract: A recording unit records an analysis operation of an image analysis model and records an adoption/non-adoption of an analysis result. As a result, a log is generated. A calculation unit calculates an adoption rate as a score indicating performance of the image analysis model based on the log. A generation unit generates, in a case where the adoption rate is smaller than a threshold value, a reference image for notifying an examiner of such a situation.

Abstract: An ultrasound diagnostic apparatus includes an ultrasound transmission and reception unit that transmits and receives ultrasound waves to and from a subject and that generates a reception signal, an ultrasound information generation unit that generates a plurality of types of ultrasound information based on the reception signal, a detection and measurement unit that detects and measures a lesion based on the plurality of types of ultrasound information, and a lesion/risk information analysis unit that analyzes a state of the lesion based on a measurement result obtained by the detection and measurement unit. The detection and measurement unit includes at least one of a set of a tumorous lesion detection unit and a tumorous lesion measurement unit, a set of a fibrotic lesion detection unit and a fibrotic lesion measurement unit, a set of a calcified lesion detection unit and a calcified lesion measurement unit, or a set of a fatty liver detection unit and a fatty liver measurement unit.

Abstract: An ultrasound diagnostic apparatus includes an ultrasound transmission and reception unit that transmits and receives ultrasound waves to and from a subject and that generates a reception signal, an ultrasound information generation unit that generates a plurality of types of ultrasound information based on the reception signal, a detection and measurement unit that detects and measures a lesion based on the plurality of types of ultrasound information, and a lesion/risk information analysis unit that analyzes a state of the lesion based on a measurement result obtained by the detection and measurement unit. The detection and measurement unit includes at least one of a set of a mass lesion detection unit and a mass lesion measurement unit, or a set of a calcified lesion detection unit and a calcified lesion measurement unit.

Abstract: A mark that identifies a lesion site is displayed on a tomographic image. A two-dimensional map and a graph are displayed regardless of whether or not the mark is displayed. The two-dimensional map represents lesion site probability distribution. The graph represents temporal change of lesion site probabilities.

Abstract: To provide a medical image processing apparatus and a medical image processing method enabling a reduction in burden of re-imaging and re-interpretation of a medical image. The medical image processing apparatus for processing a medical image includes: a detection section that detects, from the medical image, a candidate region which is a region including a lesion candidate or target tissue, and that calculates an identification score for the candidate region; a designated region acquisition section that acquires a designated region which is a region designated by an operator; and a redetection section that calculates an identification score for the designated region based on the designated region and multiple predefined regions which are regions used in a process of detecting the candidate region.

Abstract: In medical examination of breast cancer, a lesion computer-aided detection is performed in real time and with high accuracy, and a burden on a medical worker is reduced. A medical image processing apparatus that processes a medical image includes: a detection unit configured to detect a lesion candidate region; a validity evaluation unit configured to evaluate validity of the lesion candidate region by using a normal tissue region corresponding to the detected lesion candidate region; and a display unit configured to determine display content to a user by using an evaluation result.

Abstract: A detection unit detects a lesion candidate contained in display frame data (a tomographic image), using a machine learned detection model. An exclusion processing unit collates a feature vector of the detected lesion candidate with feature vectors registered in an exclusion database to determine whether the detected lesion candidate is an exclusion target. When the detected lesion candidate is an exclusion target, a mark display control unit restricts display of a mark for indicating a lesion candidate.

Abstract: An object of the invention is to provide a user with information that serves as a material for determining whether an image generated by processing including a neural network is valid. A reception signal output by an ultrasonic probe that has received an ultrasonic wave from a subject is received, and an ultrasonic image is generated based on the reception signal. A trained neural network receives the reception signal or the ultrasonic image, and outputs an estimated reception signal or an estimated ultrasonic image. A validity information generation unit generates information indicating validity of the estimated reception signal or the estimated ultrasonic image by using one or more of the reception signal, the ultrasonic image, the estimated reception signal, the estimated ultrasonic image, and output of an intermediate layer of the neural network.

Abstract: In medical examination of breast cancer, a lesion computer-aided detection is performed in real time and with high accuracy, and a burden on a medical worker is reduced. A medical image processing apparatus that processes a medical image includes: a detection unit configured to detect a lesion candidate region; a validity evaluation unit configured to evaluate validity of the lesion candidate region by using a normal tissue region corresponding to the detected lesion candidate region; and a display unit configured to determine display content to a user by using an evaluation result.

Abstract: To provide a medical image processing apparatus and a medical image processing method enabling a reduction in burden of re-imaging and re-interpretation of a medical image. The medical image processing apparatus for processing a medical image includes: a detection section that detects, from the medical image, a candidate region which is a region including a lesion candidate or target tissue, and that calculates an identification score for the candidate region; a designated region acquisition section that acquires a designated region which is a region designated by an operator; and a redetection section that calculates an identification score for the designated region based on the designated region and multiple predefined regions which are regions used in a process of detecting the candidate region.

Abstract: An ultrasound diagnosis apparatus includes a processor for performing grouping processing and representative frame selection processing on a plurality of ultrasound frames that are sequentially generated with the passage of time. The grouping processing is processing that identifies a group of interest that is composed of a plurality of frames that satisfy at least one predetermined condition of interest. The representative frame selection processing is processing that selects a representative frame from among the plurality of frames that constitute the group of interest. The at least one predetermined condition of interest includes a condition that each of the plurality of frames includes data indicating a specific region identified by region recognition processing in which a characteristic region in an image is recognized as the specific region. The representative frame selection processing includes processing that selects the representative frame based on geometrical properties of the specific regions.

Abstract: An object of the invention is to provide a user with information that serves as a material for determining whether an image generated by processing including a neural network is valid. A reception signal output by an ultrasonic probe that has received an ultrasonic wave from a subject is received, and an ultrasonic image is generated based on the reception signal. A trained neural network receives the reception signal or the ultrasonic image, and outputs an estimated reception signal or an estimated ultrasonic image. A validity information generation unit generates information indicating validity of the estimated reception signal or the estimated ultrasonic image by using one or more of the reception signal, the ultrasonic image, the estimated reception signal, the estimated ultrasonic image, and output of an intermediate layer of the neural network.

Abstract: Provided is a medical diagnosis device that further increases the reliability of measurement results on the basis of an image of a subject. The medical diagnosis device is characterized by being provided with: an image generation unit that generates an image of a subject; an auxiliary information generation unit that generates auxiliary information on the basis of input from an operation unit; a measurement computation unit that computes a measurement position using the image generated by the image generation unit, the auxiliary information, and measurement conditions, and computes measurement values using the image generated by the image generation unit and the computed measurement position; and a display unit that displays the image generated by the image generation unit, the input position information, and the measurement value computed by the measurement computation unit.

Abstract: Apparatus and method of medical diagnostic imaging. The apparatus includes: an image unit for constructing volume image data by capturing images from a multiplicity of tomographic images of a sampling specimen and for constructing internal three dimensional images of the diagnosing object of the sampling specimen as seen from a viewing point; a display for displaying the three-dimensional images; an input unit for entering parameters for setting up a precutting plane at an inter-voxel image data boundary between voxel image data of the volume image data closer to the viewing point than the diagnosing object and voxel image data associated with the diagnosing object; and a control unit for controlling the structure of the three-dimensional images constructed by the image unit based on the precutting plane set up via the input unit, wherein the control unit extracts a boundary based on one of the parameters inputted to the input unit.

Abstract: To provide an ultrasonic imaging apparatus and an ultrasound image display method capable of preventing a three-dimensional ultrasound image from flickering due to an inappropriate ROI being calculated and improving the image quality of the ultrasound image. An ultrasonic imaging apparatus of the present invention is provided with: an ROI calculating section configured to calculate an ROI from ultrasound image data; a judgment section configured to judge whether the calculation of the ROI is successful or not on the basis of at least one of a position with a predetermined brightness difference and the number of positions with the brightness difference in the ultrasound image data; and a compensation section configured to compensate a failed ultrasound image based on the ROI judged to be failed by the judgment section with a successful ultrasound image based on the ROI judged to be successful by the judgment section.

Abstract: Provided is a medical diagnosis device that further increases the reliability of measurement results on the basis of an image of a subject. The medical diagnosis device is characterized by being provided with: an image generation unit that generates an image of a subject; an auxiliary information generation unit that generates auxiliary information on the basis of input from an operation unit; a measurement computation unit that computes a measurement position using the image generated by the image generation unit, the auxiliary information, and measurement conditions, and computes measurement values using the image generated by the image generation unit and the computed measurement position; and a display unit that displays the image generated by the image generation unit, the input position information, and the measurement value computed by the measurement computation unit.

Abstract: Apparatus and method of medical diagnostic imaging. The apparatus includes: an image unit for constructing volume image data by capturing images from a multiplicity of tomographic images of a sampling specimen and for constructing internal three dimensional images of the diagnosing object of the sampling specimen as seen from a viewing point; a display for displaying the three-dimensional images; an input unit for entering parameters for setting up a precutting plane at an inter-voxel image data boundary between voxel image data of the volume image data closer to the viewing point than the diagnosing object and voxel image data associated with the diagnosing object; and a control unit for controlling the structure of the three-dimensional images constructed by the image unit based on the precutting plane set up via the input unit, wherein the control unit extracts a boundary based on one of the parameters inputted to the input unit.