Abstract: An ultrasound guidance dynamic progression method includes selecting a predetermined ultrasound diagnostic workflow in memory of an ultrasound diagnostic computing system, the workflow including a sequence of views of a target organ. The method further includes selecting a first view in the sequence and presenting guidance in a display of the computing system for the first view, for instance visual, audible or haptic feedback. The method yet further includes acquiring imagery in the computing system in association with the first view, and detecting an anomalous feature of the acquired imagery. Finally, the method includes selecting a different view in the sequence as a substitute for a next one of the views in the sequence in response to having detected the anomalous feature, and further presenting different guidance in the display for the different view in lieu of guidance for the next one of the views.

Abstract: Circuitless heart cycle determination includes capturing a video clip of one or more image frames of a target heart muscle through an ultrasound imaging device and submitting the frames to a classifier that has been trained with an annotated set of images, each of a corresponding heart muscle captured at a specified phase of a heart cycle with a ground truth indication of the specified phase of the heart cycle drawn from a separately recorded cycle graph of an electrical signal measured over time for the corresponding heart muscle. In response to the submission, a classification is received of different portions of the submitted frames according to corresponding phases of the heart cycle. Finally, a contemporaneous phase of the heart cycle is determined in the device for the target heart muscle without sensing electrical signals by way of a closed-loop sensor circuit affixed proximately to the target heart muscle.

Abstract: Embodiments of the present invention provide a method, system and computer program product for ultrasound image acquisition optimization according to different respiration modes. A method for ultrasound image acquisition optimization according to different respiration modes includes acquiring by an ultrasound imaging device, an ultrasound image of a target organ. The method further includes comparing attributes of the acquired ultrasound image to association data in a data store of associations associating attributes of previously acquired ultrasound imagery of different images of the target organ with different modes of respiration. Finally, the method includes determining from the comparison, a mode of respiration evident from the acquired ultrasound image and presenting the determined mode in the ultrasound imaging device.

Abstract: A method for clip selection includes receiving through an interface to a medical imaging device, a selection of a diagnostic procedure and a target portion of a mammalian body. Thereafter, the device acquires video clip imagery of the target portion and stores the video clip imagery in an image store. Each video clip of the video clip imagery is then image processed to determine a view and a quality of each video clip and a rule is retrieved from a rules base corresponding to the selected diagnostic procedure and target portion. In this regard, the rule specifies a requisite view and quality of the video clip imagery. Finally, the retrieved rule is applied to the video clip imagery as a filter to produce a subset of video clip imagery satisfying the specified requisite view and quality and the subset of video clip imagery is stored in the image store.

Abstract: The continuous and dynamic computation of ejection fraction (EF) includes training a neural network with different sets of cardiac imaging data acquired of a ventricle for different hearts and a known EF for each of the sets and then loading the trained neural network into memory of a computer. Afterwards, contemporaneous sets of imaging data of a ventricle of a heart are continuously acquired according to a specified view. For each corresponding set of imaging data, an image quality value may then be computed, and the corresponding set of imaging data may be provided to the neural network. The neural network, in response, provides, as output, an EF determination output without tracing a ventricle boundary of the heart. Thereafter, both the computed image quality value and the EF determination output may be displayed in a display of the computer.

Abstract: A method for clip selection includes receiving through an interface to a medical imaging device, a selection of a diagnostic procedure and a target portion of a mammalian body. Thereafter, the device acquires video clip imagery of the target portion and stores the video clip imagery in an image store. Each video clip of the video clip imagery is then image processed to determine a view and a quality of each video clip and a rule is retrieved from a rules base corresponding to the selected diagnostic procedure and target portion. In this regard, the rule specifies a requisite view and quality of the video clip imagery. Finally, the retrieved rule is applied to the video clip imagery as a filter to produce a subset of video clip imagery satisfying the specified requisite view and quality and the subset of video clip imagery is stored in the image store.

Abstract: A method for clip selection includes receiving through an interface to a medical imaging device, a selection of a diagnostic procedure and a target portion of a mammalian body. Thereafter, the device acquires video clip imagery of the target portion and stores the video clip imagery in an image store. Each video clip of the video clip imagery is then image processed to determine a view and a quality of each video clip and a rule is retrieved from a rules base corresponding to the selected diagnostic procedure and target portion. In this regard, the rule specifies a requisite view and quality of the video clip imagery. Finally, the retrieved rule is applied to the video clip imagery as a filter to produce a subset of video clip imagery satisfying the specified requisite view and quality and the subset of video clip imagery is stored in the image store.

Abstract: A method for clip selection includes receiving through an interface to a medical imaging device, a selection of a diagnostic procedure and a target portion of a mammalian body. Thereafter, the device acquires video clip imagery of the target portion and stores the video clip imagery in an image store. Each video clip of the video clip imagery is then image processed to determine a view and a quality of each video clip and a rule is retrieved from a rules base corresponding to the selected diagnostic procedure and target portion. In this regard, the rule specifies a requisite view and quality of the video clip imagery. Finally, the retrieved rule is applied to the video clip imagery as a filter to produce a subset of video clip imagery satisfying the specified requisite view and quality and the subset of video clip imagery is stored in the image store.

Abstract: Embodiments of the present invention provide a method, system and computer program product for ultrasound image acquisition optimization according to different respiration modes. A method for ultrasound image acquisition optimization according to different respiration modes includes acquiring by an ultrasound imaging device, an ultrasound image of a target organ. The method further includes comparing attributes of the acquired ultrasound image to association data in a data store of associations associating attributes of previously acquired ultrasound imagery of different images of the target organ with different modes of respiration. Finally, the method includes determining from the comparison, a mode of respiration evident from the acquired ultrasound image and presenting the determined mode in the ultrasound imaging device.

Abstract: A method for clip selection includes receiving through an interface to a medical imaging device, a selection of a diagnostic procedure and a target portion of a mammalian body. Thereafter, the device acquires video clip imagery of the target portion and stores the video clip imagery in an image store. Each video clip of the video clip imagery is then image processed to determine a view and a quality of each video clip and a rule is retrieved from a rules base corresponding to the selected diagnostic procedure and target portion. In this regard, the rule specifies a requisite view and quality of the video clip imagery. Finally, the retrieved rule is applied to the video clip imagery as a filter to produce a subset of video clip imagery satisfying the specified requisite view and quality and the subset of video clip imagery is stored in the image store.

Abstract: A method for clip selection includes receiving through an interface to a medical imaging device, a selection of a diagnostic procedure and a target portion of a mammalian body. Thereafter, the device acquires video clip imagery of the target portion and stores the video clip imagery in an image store. Each video clip of the video clip imagery is then image processed to determine a view and a quality of each video clip and a rule is retrieved from a rules base corresponding to the selected diagnostic procedure and target portion. In this regard, the rule specifies a requisite view and quality of the video clip imagery. Finally, the retrieved rule is applied to the video clip imagery as a filter to produce a subset of video clip imagery satisfying the specified requisite view and quality and the subset of video clip imagery is stored in the image store.

Abstract: A saliency mapping method includes displaying video clip imagery of an organ in a display of a computer and submitting the imagery to a neural network trained to produce a probability of an existence of a physical feature of the organ. In response, the probability is received along with a pixel-wise mapping of dispositive pixels in the imagery resulting in the probability. Variations of the imagery are then repeatedly resubmitted to the neural network, each including a change to one or more of the pixels in the imagery. Thereafter, for each resubmission, a change is measured in the probability and then correlated to the changed pixels. Finally, a graphical indicator is overlain on the display of the imagery corresponding to each of the pixels determined through the repeated resubmission to be dispositive based upon a threshold measured change in probability.

Abstract: An ultrasound guidance dynamic mode switching method includes selecting a predetermined ultrasound diagnostic procedure in memory of an ultrasound diagnostic computing system and identifying an operating mode of the system for a first sequence of views stored in the memory as a workflow in correspondence to the selected procedure. The method additionally includes placing the system in the identified operating mode and acquiring imagery of a target organ in association with the views of the first sequence of the workflow. Finally, the method includes detecting in the acquired imagery, a feature of the target organ mapped to a different operating mode, and in response to the detection, displaying a recommendation in a display to change operating modes, placing the system into the different operating mode, and acquiring additional imagery of the target organ utilizing the system in association with a different sequence of additional views of a different workflow.

Abstract: An ultrasound guidance dynamic progression method includes selecting a predetermined ultrasound diagnostic workflow in memory of an ultrasound diagnostic computing system, the workflow including a sequence of views of a target organ. The method further includes selecting a first view in the sequence and presenting guidance in a display of the computing system for the first view, for instance visual, audible or haptic feedback. The method yet further includes acquiring imagery in the computing system in association with the first view, and detecting an anomalous feature of the acquired imagery. Finally, the method includes selecting a different view in the sequence as a substitute for a next one of the views in the sequence in response to having detected the anomalous feature, and further presenting different guidance in the display for the different view in lieu of guidance for the next one of the views.

Abstract: A method for clip selection includes receiving through an interface to a medical imaging device, a selection of a diagnostic procedure and a target portion of a mammalian body. Thereafter, the device acquires video clip imagery of the target portion and stores the video clip imagery in an image store. Each video clip of the video clip imagery is then image processed to determine a view and a quality of each video clip and a rule is retrieved from a rules base corresponding to the selected diagnostic procedure and target portion. In this regard, the rule specifies a requisite view and quality of the video clip imagery. Finally, the retrieved rule is applied to the video clip imagery as a filter to produce a subset of video clip imagery satisfying the specified requisite view and quality and the subset of video clip imagery is stored in the image store.

Abstract: A method for clip selection includes receiving through an interface to a medical imaging device, a selection of a diagnostic procedure and a target portion of a mammalian body. Thereafter, the device acquires video clip imagery of the target portion and stores the video clip imagery in an image store. Each video clip of the video clip imagery is then image processed to determine a view and a quality of each video clip and a rule is retrieved from a rules base corresponding to the selected diagnostic procedure and target portion. In this regard, the rule specifies a requisite view and quality of the video clip imagery. Finally, the retrieved rule is applied to the video clip imagery as a filter to produce a subset of video clip imagery satisfying the specified requisite view and quality and the subset of video clip imagery is stored in the image store.

Abstract: A method for prescriptively guiding an operator of an ultrasound imaging probe includes acquiring a sequence of image clips of a target organ utilizing an ultrasound imaging probe, determining a particular view of the target organ expressed by the acquired image clips and assessing a quality of each of the acquired image clips in respect to the particular view. On condition that the assessed quality falls below a pre-determined satisfactory quality for the particular view, a prescriptive movement of the probe is computed that has been pre-determined to produce quality improvement of a subsequently acquired image clip of the target organ for the particular view. Then, responsive to determining that the prescriptive movement has been computed a threshold number of times in connection with the sequence, the prescriptive movement is displayed concurrently with a display of subsequently acquired image clips of the target organ.

Abstract: A saliency mapping method includes displaying video clip imagery of an organ in a display of a computer and submitting the imagery to a neural network trained to produce a probability of an existence of a physical feature of the organ. In response, the probability is received along with a pixel-wise mapping of dispositive pixels in the imagery resulting in the probability. Variations of the imagery are then repeatedly resubmitted to the neural network, each including a change to one or more of the pixels in the imagery. Thereafter, for each resubmission, a change is measured in the probability and then correlated to the changed pixels. Finally, a graphical indicator is overlain on the display of the imagery corresponding to each of the pixels determined through the repeated resubmission to be dispositive based upon a threshold measured change in probability.

Abstract: Embodiments of the present invention provide a method, system and computer program product for video clip quality determination in medical device imaging and diagnosis. In an embodiment of the invention, a method for video clip quality determination in medical imaging includes first retrieving from a data store into memory of a host computer, video clip imagery of a target organ. Then, a quality value assigned to the video clip imagery may be identified in connection with the retrieved video clip imagery. A measurement of the target organ is computed based upon the retrieved video clip imagery. Finally, a confidence in respect to the computed measurement is determined based upon the identified quality value and the confidence determination displayed in a user interface provided by the host computer.

Abstract: A method for clip selection includes receiving through an interface to a medical imaging device, a selection of a diagnostic procedure and a target portion of a mammalian body. Thereafter, the device acquires video clip imagery of the target portion and stores the video clip imagery in an image store. Each video clip of the video clip imagery is then image processed to determine a view and a quality of each video clip and a rule is retrieved from a rules base corresponding to the selected diagnostic procedure and target portion. In this regard, the rule specifies a requisite view and quality of the video clip imagery. Finally, the retrieved rule is applied to the video clip imagery as a filter to produce a subset of video clip imagery satisfying the specified requisite view and quality and the subset of video clip imagery is stored in the image store.