Abstract: Ultrasound image devices, systems, and methods are provided. An ultrasound imaging system comprising a processor circuit configured to receive, from an ultrasound transducer array, a plurality of images of a patient body at different imaging planes; determine a first imaging plane based on a first image of the plurality of images by applying a first predictive network, wherein a second image of the plurality of images is based on the first imaging plane, and wherein the second image includes an imaging view of at least one of an anatomy of the patient body or a medical device within the anatomy; apply a second predictive network to the second image to generate segmentation data; and output, to a display, a displayed image including an indication of a first portion of the at least one of the anatomy or the medical device based on the segmentation data.

Abstract: Systems and methods for detecting placement of an object in a digital image are provided. The system receives a digital image and processes the digital image to generate one or more candidate regions within the digital image using a first neural network. The system then selects a proposed region from the one or more candidate regions using the first neural network and assigns a score to the proposed region using the first neural network. Lastly, the system processes the proposed region using a second neural network to detect an object in the proposed region.

Abstract: Computer vision systems and methods for time-aware needle tip localization in two-dimensional (2D) ultrasound images are provided. A consecutive fused image sequence, derived from fusion of the enhanced frames and the corresponding B-mode frames, is processed by a time-aware neural network which includes a unified convolutional neural network (CNN) and a long short-term memory (LSTM) recurrent neural network. The CNN acts as a feature extractor, with stacked convolutional layers which progressively create a hierarchy of more abstract features. The LSTM models temporal dependencies in time-series data. The system learns spatiotemporal features associated with needle tip movement, for example, needle tip appearance and trajectory information, and successfully localizes the needle tip in the presence of abrupt intensity changes and motion artifacts.

Abstract: Ultrasound image devices, systems, and methods are provided. An ultrasound imaging system comprising a processor circuit configured to receive, from an ultrasound transducer array, a plurality of images of a patient body at different imaging planes; determine a first imaging plane based on a first image of the plurality of images by applying a first predictive network, wherein a second image of the plurality of images is based on the first imaging plane, and wherein the second image includes an imaging view of at least one of an anatomy of the patient body or a medical device within the anatomy; apply a second predictive network to the second image to generate segmentation data; and output, to a display, a displayed image including an indication of a first portion of the at least one of the anatomy or the medical device based on the segmentation data.

Abstract: Computer vision systems and methods for real-time localization of a needle in an ultrasound video are provided. The method includes a step of receiving at a processor a plurality of frames from the ultrasound video. The method also includes the step of identifying by the processor one of the plurality of frames as a background image and a frame adjacent to the background image as a current image. The method further includes the step of performing by the processor a bitwise complement operation on the background image to generate a complement image. Moreover, the method includes the step of performing by the processor a pointwise logical AND operation on the complement image and the current image to identify the location of the needle.

Abstract: Computer vision systems and methods for real-time localization of a needle in an ultrasound video are provided. The method includes a step of receiving at a processor a plurality of frames from the ultrasound video. The method also includes the step of identifying by the processor one of the plurality of frames as a background image and a frame adjacent to the background image as a current image. The method further includes the step of performing by the processor a bitwise complement operation on the background image to generate a complement image. Moreover, the method includes the step of performing by the processor a pointwise logical AND operation on the complement image and the current image to identify the location of the needle.

Abstract: Systems and methods for detecting placement of an object in a digital image are provided. The system receives a digital image and processes the digital image to generate one or more candidate regions within the digital image using a first neural network. The system then selects a proposed region from the one or more candidate regions using the first neural network and assigns a score to the proposed region using the first neural network. Lastly, the system processes the proposed region using a second neural network to detect an object in the proposed region.