Abstract: A system and method for automatically detecting an ultrasound image view and focus to provide feedback on measurement suitability is provided. The method includes acquiring, by an ultrasound system, an ultrasound image of a target. The method includes automatically identifying, by at least one processor of the ultrasound system, an ultrasound image view and focus based on detected anatomical structures in the ultrasound image. The method includes automatically selecting, by the at least one processor, at least one measurement associated with the ultrasound image view. The method includes assigning, by the at least one processor, a measurement grade for each of the at least one measurements based on an ability to accurately perform each of the at least one measurement in the ultrasound image. The method includes causing, by the at least one processor, a display system to present the measurement grade for each of the at least one measurement.

Abstract: Systems and methods for defining a boundary of a region of interest in an ultrasound image are provided. The method includes receiving an ultrasound image having pixels and automatically processing the ultrasound image to output a probability of each of the pixels being in a region of interest. The method includes applying a first threshold value to determine a boundary of the region of interest. The first threshold value corresponds with a first segmentation sensitivity level of a plurality of segmentation sensitivity levels. The method includes displaying the ultrasound image with the boundary overlaid on the ultrasound image. The method includes receiving a user selection of a second segmentation sensitivity level that corresponds with a second threshold value different from the first threshold value, and dynamically updating the boundary overlaid on the ultrasound image at the display based on the second threshold value.

Abstract: Systems and methods for automatically detecting two-dimensional standard views in transesophageal ultrasound images are provided. The method includes acquiring a first ultrasound image at a first depth and a first omniplane angle. The first ultrasound image corresponds with a first standard view. The first omniplane angle is an angle different from zero (0) degrees. The method includes adjusting the first omniplane angle to a second omniplane angle of 0 degrees. The method includes acquiring a second ultrasound image at the first depth with the second omniplane angle. The method includes automatically analyzing the second ultrasound image to identify a second standard view corresponding with the second omniplane angle. The method includes automatically determining the first standard view based on the second standard view and the first omniplane angle. The method includes causing a display system to present the first ultrasound image with a first identifier of the first standard view.

Abstract: A system and method for automatically detecting an ultrasound image view and focus to provide feedback on measurement suitability is provided. The method includes acquiring, by an ultrasound system, an ultrasound image of a target. The method includes automatically identifying, by at least one processor of the ultrasound system, an ultrasound image view and focus based on detected anatomical structures in the ultrasound image. The method includes automatically selecting, by the at least one processor, at least one measurement associated with the ultrasound image view. The method includes assigning, by the at least one processor, a measurement grade for each of the at least one measurements based on an ability to accurately perform each of the at least one measurement in the ultrasound image. The method includes causing, by the at least one processor, a display system to present the measurement grade for each of the at least one measurement.

Abstract: A system and method for automatically detecting an apex point in apical ultrasound image views to provide a foreshortening warning is provided. The method may include acquiring, by an ultrasound system, apical ultrasound image views over a time period. The method may include automatically detecting, by at least one processor, an apical point in the apical ultrasound image views. The method may include determining, by the at least one processor, an amount of movement of the apical point in the apical ultrasound image views over the time period. The method may include causing, by the at least one processor, a display system to present the apical ultrasound image views with a foreshortening warning when the amount of movement of the apical point in the apical ultrasound image views over the time period exceeds a threshold.

Abstract: Continuous training of an artificial intelligence (AI) model for an ultrasound scanner is provided. A method for the training comprises generating an image of a target using an AI model, detecting, by a processor, a correction of the target image by an operator. One or both of the following may be saved: the corrected image, and the target image and correction data to the target image. The ultrasound scanner may initiate training the AI model using one of: the corrected image and the target image and correction data for the target image.

Abstract: Systems and methods for prompting data donation for artificial intelligence tool development are provided. The method includes presenting an ultrasound image and at least one automated analysis feature at a display system. The at least one automated analysis feature includes one or more non-enabled automated analysis features. The method includes receiving a user selection of at least one of the one or more non-enabled automated analysis features. The method includes presenting at the display system a prompt providing a user option to share user analysis data. The method includes receiving a user selection opting to share the user analysis data. The method includes providing access to the at least one of the one or more non-enabled automated analysis features when a condition is met.