Abstract: A method of creating and displaying a visually distinct rendering of an ultrasound image, acquired from an ultrasound scanner, comprises deploying an AI model which is trained to identify and segment boundaries of a feature or features, in whole or part, acquiring, at the computing device, a new ultrasound image during ultrasound scanning, processing, using the AI model, the new ultrasound image to identify and segment boundaries of a single feature or two or more features, in whole or part, on the new ultrasound image, thereby creating a single segmented boundary feature or two or more segmented boundary features, applying a graphic onto the single segmented boundary feature or the at least two segmented boundary features, thereby forming a graphic feature image and generating an output image, on the screen, comprising the graphic feature image.

Abstract: A method of creating and displaying a visually distinct rendering of an ultrasound image, acquired from an ultrasound scanner, comprises displaying, on a screen that is communicatively connected to the ultrasound scanner, an ultrasound image feed comprising ultrasound image frames, deploying an AI model to execute on a computing device communicably connected to the ultrasound scanner, wherein the AI model is trained so that when the AI model is deployed, the computing device identifies and segments boundaries of a feature or features, in whole or part, acquiring, at the computing device, a new ultrasound image during ultrasound scanning, processing, using the AI model, the new ultrasound image to identify and segment boundaries of a single feature or two or more features, in whole or part, on the new ultrasound image, thereby creating a single segmented boundary feature or two or more segmented boundary features, applying a graphic onto the single segmented boundary feature or the at least two segmented bound

Abstract: A method for automatically measuring a bladder on an ultrasound image feed comprises deploying an AI model which is trained so that when the AI model is deployed, the computing device identifies and predicts a view of the bladder, from one of a sagittal view and a transverse view; and when a new ultrasound image is processed, using the AI model identifies and predicts the view of the bladder, wherein the prediction is an AI model output; wherein if the AI model output predicts a sagittal view of the bladder, automatically applying one caliper set along a superior-inferior dimension of the bladder and measuring the superior-inferior dimension; and if the AI model output predicts a transverse view of the bladder, applying two caliper sets along each of a length and a width of the bladder and measuring the length and width thereof.

Abstract: A method for automatically measuring a bladder on an ultrasound image feed, acquired from an ultrasound scanner comprises displaying, on a screen that is communicatively connected to the ultrasound scanner, the ultrasound image feed comprising ultrasound image frames of a bladder; deploying an AI model to execute on a computing device communicably connected to the ultrasound scanner, wherein the AI model is trained so that when the AI model is deployed, the computing device identifies and predicts a view of the bladder, from one of a sagittal view and a transverse view; acquiring, at the computing device, a new ultrasound image during ultrasound scanning; processing, using the AI model, the new ultrasound image to identify and predict the view of the bladder, wherein the prediction is an AI model output; wherein if f the AI model output predicts that the new ultrasound image comprises a sagittal view of the bladder, automatically applying one caliper set along a superior-inferior dimension of the bladder and

Abstract: A method for automatically measuring a bladder on an ultrasound image feed, acquired from an ultrasound scanner comprises displaying, on a screen that is communicatively connected to the ultrasound scanner, the ultrasound image feed comprising ultrasound image frames of a bladder; deploying an AI model to execute on a computing device communicably connected to the ultrasound scanner, wherein the AI model is trained so that when the AI model is deployed, the computing device identifies and predicts a view of the bladder, from one of a sagittal view and a transverse view; acquiring, at the computing device, a new ultrasound image during ultrasound scanning; processing, using the AI model, the new ultrasound image to identify and predict the view of the bladder, wherein the prediction is an AI model output; wherein if f the AI model output predicts that the new ultrasound image comprises a sagittal view of the bladder, automatically applying one caliper set along a superior-inferior dimension of the bladder and

Abstract: A method of creating and displaying a visually distinct rendering of an ultrasound image, acquired from an ultrasound scanner, comprises displaying, on a screen that is communicatively connected to the ultrasound scanner, an ultrasound image feed comprising ultrasound image frames, deploying an AI model to execute on a computing device communicably connected to the ultrasound scanner, wherein the AI model is trained so that when the AI model is deployed, the computing device identifies and segments boundaries of a feature or features, in whole or part, acquiring, at the computing device, a new ultrasound image during ultrasound scanning, processing, using the AI model, the new ultrasound image to identify and segment boundaries of a single feature or two or more features, in whole or part, on the new ultrasound image, thereby creating a single segmented boundary feature or two or more segmented boundary features, applying a graphic onto the single segmented boundary feature or the at least two segmented bound