Abstract: The invention provides a method for making anatomical measurements using a captured ultrasound image representative of the anatomical region of interest. The method comprises receiving (20) data representative of a set of points selected by a user within the image and interpreting from the points a particular anatomical measurement type which the user is intending to perform. In particular, the points are processed to identify (24) a pattern or other geometrical characteristic of the points, and the location (22) of at least one of the points within the image is also identified. These two characteristics are used to identify from the set of points which measurement the operator is performing. Once the measurement is identified, an appropriate measurement template (26) is selected and applied in order to derive (30) from the set of points an anatomical measurement.

Abstract: A system for generating ultrasound data in respect of an anatomical body being scanned makes use of a predetermined scan protocol, which specifies a sequence of types of ultrasound scan of structures of interest. These types may for example be different imaging modalities (static, dynamic, 2D, 3D etc.) which are most appropriate for viewing different structures within the anatomical body. From received ultrasound images, a model is used to identify the structures of interest within the ultrasound images. The best images for creating the types of scan of the protocol are then identified and a sequence is compiled of those best images. In this way, a sequence is created which combines different types of scan, in a structured way according to a predetermined protocol. This makes the analysis of the sequence most intuitive for a user, and simplifies comparison between different sequences.

Abstract: An ultrasound imaging system for acquiring ultrasound images of an anatomical feature of interest in a subject, comprising a controller operable by a user and configured to: process input ultrasound images to extract anatomical data; determine a set of constraints to be applied to the ultrasound images, the constraints being spatial, temporal and/or of image quality, derived from the extracted anatomical data and/or on user input; monitor the ultrasound images, as they are received, for determining their compliance with the determined constraints; and output an indication based on the determined compliance. The user can adapt the imaging process using the feedback of these indications, and can decide to stop the process based on satisfactory indications.

Abstract: An ultrasound imaging system comprises a display for displaying a received ultrasound image. A user interface is provided for receiving user commands for controlling the ultrasound imaging process, and it receives a user input which identifies a point or region of the displayed ultrasound image. An image depth is determined which is associated with the identified point or region and the imaging process is controlled to tailor the imaging to the identified point or region.

Abstract: An ultrasound imaging system includes a processor circuit in communication with an ultrasound transducer configured to receive three-dimensional ultrasound data of an anatomy, and generate a target image corresponding to a target image plane of the anatomy, and a plurality of adjacent images corresponding to image planes adjacent to the target image plane along a simulated motion path. The processor circuit is further configured to display the target image, receive a user input representative of a direction of motion along the simulated motion path, and display an adjacent image of the plurality of adjacent images corresponding to the direction of motion. Accordingly, the user can observe the target image in its spatial context by scanning through the target image and one or more adjacent images on the display as if the ultrasound transducer were being scanned along the simulated motion path.

Abstract: A method and system for mapping boundary detecting features of at least one source triangulated mesh of known topology to a target triangulated mesh of arbitrary topology. A region of interest in a volumetric image associated with each triangle of the target triangulated mesh is provided to a feature mapping network. The feature mapping network assigns a feature selection vector to each triangle of the target triangulated mesh. The associated region of interest and assigned feature selection vector for each triangle of the target triangulated mesh are provided to a boundary detection network. A predicted boundary based on features of the associated region of interest selected by the assigned feature selection vector is obtained from the boundary detection network.

Abstract: A system for recording ultrasound images comprises a memory comprising instruction data representing a set of instructions and a processor configured to communicate with the memory and to execute the set of instructions. The set of instructions, when executed by the processor, cause the processor to receive a data stream of two dimensional images taken using an ultrasound transducer and determine from the data stream that a feature of interest is in view of the transducer. The set of instructions further cause the processor to trigger an alert to be sent to a user to indicate that the feature of interest is in view of the transducer, and send an instruction to the transducer to trigger the transducer to capture a three dimensional ultrasound image after a predetermined time interval.

Abstract: There is provided a computer implemented method (200) for medical image processing. The method comprises providing (202) a database of medical images and providing (204) an initial machine learning model which is trained for segmenting or classifying a medical feature in the medical images. The method also comprises extracting (206) a subset of medical images from the database based on a similarity score of the medical images and training (208) the machine learning model using the extracted subset of medical images in order to provide a refined machine learning model.

Abstract: An image processing system and related method. The system comprises an input interface (IN) configured for receiving an n[?2]-dimensional input image with a set of anchor points defined in same, said set of anchor points forming an input constellation. A constellation modifier (CM) is configured to modify said input constellation into a modified constellation. A constellation evaluator (CE) configured to evaluate said input constellation based on said hyper-surface to produce a score. A comparator (COMP) is configured to compare said score against a quality criterion. Through an output interface (OUT) said constellation is output if the score meets said criterion. The constellation suitable to define a segmentation for said input image.

Abstract: The invention provides a method for guiding the acquisition of an ultrasound image. A 3D ultrasound image is acquired by an ultrasound probe at a first position and an anatomical structure is identified within the 3D ultrasound image. A target imaging plane is estimated based on the identified anatomical structure and it is determined whether the target imaging plane is present within the 3D ultrasound image. If the target imaging plane is present, a displacement between a central plane of the 3D ultrasound image and the target plane is determined. If the displacement is below a predetermined threshold, the target imaging plane is extracted and if the displacement is above the predetermined threshold, an instruction to acquire a 3D ultrasound image with the ultrasound probe at a second position, different from the first position, is generated based on the displacement. The invention further provides a method for estimating a target imaging plane.

Abstract: An image processing system and related method. The system comprises an input interface (IN) configured for receiving an n[?2]-dimensional input image with a set of anchor points defined in same, said set of anchor points forming an input constellation. A constellation modifier (CM) is configured to modify said input constellation into a modified constellation. A constellation evaluator (CE) configured to evaluate said input constellation based on said hyper-surface to produce a score. A comparator (COMP) is configured to compare said score against a quality criterion. Through an output interface (OUT) said constellation is output if the score meets said criterion. The constellation suitable to define a segmentation for said input image.

Abstract: A system for generating ultrasound data in respect of an anatomical body being scanned makes use of a predetermined scan protocol, which specifies a sequence of types of ultrasound scan of structures of interest. These types may for example be different imaging modalities (static, dynamic, 2D, 3D etc.) which are most appropriate for viewing different structures within the anatomical body. From received ultrasound images, a model is used to identify the structures of interest within the ultrasound images. The best images for creating the types of scan of the protocol are then identified and a sequence is compiled of those best images. In this way, a sequence is created which combines different types of scan, in a structured way according to a predetermined protocol. This makes the analysis of the sequence most intuitive for a user, and simplifies comparison between different sequences.

Abstract: An ultrasound imaging system for acquiring ultrasound images of an anatomical feature of interest in a subject, comprising a controller operable by a user and configured to: process input ultrasound images to extract anatomical data; determine a set of constraints to be applied to the ultrasound images, the constraints being spatial, temporal and/or of image quality, derived from the extracted anatomical data and/or on user input; monitor the ultrasound images, as they are received, for determining their compliance with the determined constraints; and output an indication based on the determined compliance. The user can adapt the imaging process using the feedback of these indications, and can decide to stop the process based on satisfactory indications.

Abstract: A method and apparatus for segmenting a two-dimensional image of an anatomical structure includes acquiring (202) a three-dimensional model of the anatomical structure. The three-dimensional model includes a plurality of segments. The acquired three-dimensional model is adapted to align the acquired three-dimensional model with the two-dimensional image (204). The two-dimensional image is segmented by the plurality of segments of the adapted three-dimensional model.

Abstract: The invention provides a method for making anatomical measurements using a captured ultrasound image representative of the anatomical region of interest. The method comprises receiving (20) data representative of a set of points selected by a user within the image and interpreting from the points a particular anatomical measurement type which the user is intending to perform. In particular, the points are processed to identify (24) a pattern or other geometrical characteristic of the points, and the location (22) of at least one of the points within the image is also identified. These two characteristics are used to identify from the set of points which measurement the operator is performing. Once the measurement is identified, an appropriate measurement template (26) is selected and applied in order to derive (30) from the set of points an anatomical measurement.

Abstract: An ultrasound imaging system comprises a display for displaying a received ultrasound image. A user interface is provided for receiving user commands for controlling the ultrasound imaging process, and it receives a user input which identifies a point or region of the displayed ultrasound image. An image depth is determined which is associated with the identified point or region and the imaging process is controlled to tailor the imaging to the identified point or region.

Abstract: There is provided a computer implemented method (200) for medical image processing. The method comprises providing (202) a database of medical images and providing (204) an initial machine learning model which is trained for segmenting or classifying a medical feature in the medical images. The method also comprises extracting (206) a subset of medical images from the database based on a similarity score of the medical images and training (208) the machine learning model using the extracted subset of medical images in order to provide a refined machine learning model.

Abstract: There is provided a method and apparatus for segmenting a two-dimensional image of an anatomical structure. A three-dimensional model of the anatomical structure is acquired (202). The three-dimensional model comprises a plurality of segments. The acquired three-dimensional model is adapted to align the acquired three-dimensional model with the two-dimensional image (204). The two-dimensional image is segmented by the plurality of segments of the adapted three-dimensional model.

Abstract: A system and method are provided for displaying medical images. A first viewport is generated which shows a part of a first medical image which shows a region of interest. A second viewport is generated which shows a part of a second medical image which shows a corresponding region of interest, e.g., representing a same anatomical structure or a same type of anatomical structure. In order to establish this ‘synchronized’ display of regions of interest, a displacement field is estimated between the first medical image and the second medical image. However, the displacement field is not used to deform the second medical image. Rather, the displacement field is used to identify the corresponding region of interest and thereby which part of the second medical image is to be shown. It is thus avoided that the second medical image itself is deformed, which would typically also deform the region of interest and thereby impair its assessment.