Abstract: Apparatus, systems, and methods to deliver point of care alerts for radiological findings are disclosed. An example imaging apparatus includes an image data store, an image quality checker, and a training learning network. The example image data store is to store image data acquired using the imaging apparatus. The example image quality checker is to evaluate image data from the image data store in comparison to an image quality measure. The example trained learning network is to process the image data to identify a clinical finding in the image data, the identification of a clinical finding to trigger a notification at the imaging apparatus to notify a healthcare practitioner regarding the clinical finding and prompt a responsive action with respect to a patient associated with the image data.

Abstract: Apparatus, systems, and methods to capture and combine patient vitals and image data are disclosed. An example apparatus includes an imaging device to capture imaging data of a patient; a patient monitor to capture non-imaging data of the patient; and a communication interface between the imaging device and the patient monitor to route the non-imaging data to the imaging device. The example imaging device is to combine the non-imaging data with the imaging data to form a combined data set to be processed to determine a clinical outcome.

Abstract: Various methods and systems are provided for x-ray imaging. In one embodiment, a method for an image pasting examination comprises acquiring, via an optical camera and/or depth camera, image data of a subject, controlling an x-ray source and an x-ray detector according to the image data to acquire a plurality of x-ray images of the subject, and stitching the plurality of x-ray images into a single x-ray image. In this way, optimal exposure techniques may be used for individual acquisitions in an image pasting examination such that the optimal dose is utilized, stitching quality is improved, and registration failures are avoided.

Abstract: Apparatus, systems, and methods to improve imaging quality control, image processing, identification of findings, and generation of notification at or near a point of care are disclosed and described. An example imaging apparatus includes a processor to at least: process the first image data using a trained learning network to generate a first analysis of the first image data; identify a clinical finding in the first image data based on the first analysis; compare the first analysis to a second analysis, the second analysis generated from second image data obtained in a second image acquisition; and, when comparing identifies a change between the first analysis and the second analysis, generate a notification at the imaging apparatus regarding the clinical finding to trigger a responsive action.

Abstract: Apparatus, systems, and methods to improve imaging quality control, image processing, identification of findings, and generation of notification at or near a point of care are disclosed and described. An example imaging apparatus includes a processor to at least: process the first image data using a trained learning network to generate a first analysis of the first image data; identify a clinical finding in the first image data based on the first analysis; compare the first analysis to a second analysis, the second analysis generated from second image data obtained in a second image acquisition; and, when comparing identifies a change between the first analysis and the second analysis, generate a notification at the imaging apparatus regarding the clinical finding to trigger a responsive action.

Abstract: Methods and systems are provided for tuning a static model with multiple operating points to adjust model performance without retraining the model or triggering a new regulatory clearance. In one embodiment, a method comprises, responsive to a request to tune a model, obtaining a tuning dataset including a set of medical images, executing the model using the set of medical images as input to generate model tuning output, and determining, for each operating point of a set of operating points, a set of tuning metric values based on the tuning dataset and the model tuning output relative to each operating point. An operating point from the set of operating points may be selected based on each set of tuning metric values and, upon a request to analyze a subsequent medical image, a representation of a finding output from the static model executed at the selected operating point.

Abstract: Methods and systems are provided for wirelessly communicating between a host device and a client device in a radio frequency (RF) environment. In one embodiment, a wireless communication method for a host device in a RF environment may comprise: communicating wirelessly between the host device and a client device by way of a first RF channel; continuously scanning available RF channels of the RF environment; and in response to a first RF channel signal quality decreasing below a threshold signal quality, selecting one of the available RF channels having a signal quality greater than the threshold signal quality, and switching wireless communication between the client device and the host device from the first RF channel to the selected available RF channel. In this way, reducing interference with the RF environment while lowering a risk of disrupting the wireless communication between the host device and the client device can be achieved.

Abstract: Various methods and systems are provided for x-ray imaging. In one embodiment, a method for an image pasting examination comprises acquiring, via an optical camera and/or depth camera, image data of a subject, controlling an x-ray source and an x-ray detector according to the image data to acquire a plurality of x-ray images of the subject, and stitching the plurality of x-ray images into a single x-ray image. In this way, optimal exposure techniques may be used for individual acquisitions in an image pasting examination such that the optimal dose is utilized, stitching quality is improved, and registration failures are avoided.

Abstract: Apparatus, systems, and methods to improve imaging quality control, image processing, identification of findings in image data, and generation of notification at or near a point of care for a patient are disclosed and described. An example imaging apparatus includes a memory including chest image data and instructions and a processor. The example processor is to execute the instructions to at least: process the chest image data using a trained learning network in real time after acquisition of the chest image data to identify a pneumothorax in the chest image data; receive feedback regarding the identification of the pneumothorax; and, when the feedback confirms the identification of the pneumothorax, trigger a notification at the imaging apparatus to notify a healthcare practitioner regarding the pneumothorax and prompt a responsive action with respect to a patient associated with the chest image data.

Abstract: Methods and systems are provided for wirelessly communicating between a host device and a client device in a radio frequency (RF) environment. In one embodiment, a wireless communication method for a host device in a RF environment may comprise: communicating wirelessly between the host device and a client device by way of a first RF channel; continuously scanning available RF channels of the RF environment; and in response to a first RF channel signal quality decreasing below a threshold signal quality, selecting one of the available RF channels having a signal quality greater than the threshold signal quality, and switching wireless communication between the client device and the host device from the first RF channel to the selected available RF channel. In this way, reducing interference with the RF environment while lowering a risk of disrupting the wireless communication between the host device and the client device can be achieved.

Abstract: Apparatus, systems, and methods to deliver point of care alerts for radiological findings are disclosed. An example imaging apparatus includes an image data store, an image quality checker, and a training learning network. The example image data store is to store image data acquired using the imaging apparatus. The example image quality checker is to evaluate image data from the image data store in comparison to an image quality measure. The example trained learning network is to process the image data to identify a clinical finding in the image data, the identification of a clinical finding to trigger a notification at the imaging apparatus to notify a healthcare practitioner regarding the clinical finding and prompt a responsive action with respect to a patient associated with the image data.

Abstract: Apparatus, systems, and methods to improve imaging quality control, image processing, identification of findings, and generation of notification at or near a point of care are disclosed and described. An example imaging apparatus includes a processor to at least: process the first image data using a trained learning network to generate a first analysis of the first image data; identify a clinical finding in the first image data based on the first analysis; compare the first analysis to a second analysis, the second analysis generated from second image data obtained in a second image acquisition; and, when comparing identifies a change between the first analysis and the second analysis, generate a notification at the imaging apparatus regarding the clinical finding to trigger a responsive action.

Abstract: Various methods and systems are provided for x-ray imaging. In one embodiment, a method for an image pasting examination comprises acquiring, via an optical camera and/or depth camera, image data of a subject, controlling an x-ray source and an x-ray detector according to the image data to acquire a plurality of x-ray images of the subject, and stitching the plurality of x-ray images into a single x-ray image. In this way, optimal exposure techniques may be used for individual acquisitions in an image pasting examination such that the optimal dose is utilized, stitching quality is improved, and registration failures are avoided.

Abstract: Apparatus, systems, and methods to capture and combine patient vitals and image data are disclosed. An example apparatus includes an imaging device to capture imaging data of a patient; a patient monitor to capture non-imaging data of the patient; and a communication interface between the imaging device and the patient monitor to route the non-imaging data to the imaging device. The example imaging device is to combine the non-imaging data with the imaging data to form a combined data set to be processed to determine a clinical outcome.

Abstract: Apparatus, systems, and methods to improve automated identification, monitoring, processing, and control of a condition impacting a patient using image data and artificial intelligence classification are disclosed. An example image processing apparatus includes an artificial intelligence classifier to: process first image data for a patient from a first time to determine a first classification result indicating a first severity of a condition for the patient; and process second image data for the patient from a second time to determine a second classification result indicating a second severity of the condition for the patient. The example image processing apparatus includes a comparator to compare the first classification result and the second classification result to determine a change and a progression of the condition associated with the change. The example image processing apparatus includes an output generator to trigger an action when the progression corresponds to a worsening of the condition.

Abstract: Apparatus, systems, and methods to deliver point of care alerts for radiological findings are disclosed. An example imaging apparatus includes an image data store, an image quality checker, and a training learning network. The example image data store is to store image data acquired using the imaging apparatus. The example image quality checker is to evaluate image data from the image data store in comparison to an image quality measure. The example trained learning network is to process the image data to identify a clinical finding in the image data, the identification of a clinical finding to trigger a notification at the imaging apparatus to notify a healthcare practitioner regarding the clinical finding and prompt a responsive action with respect to a patient associated with the image data.

Abstract: Apparatus, systems, and methods to improve imaging quality control, image processing, identification of findings, and generation of notification at or near a point of care are disclosed and described. An example imaging apparatus includes a processor to at least: evaluate first image data with respect to an image quality measure; when the first image data satisfies the image quality measure, process the first image data using a trained learning network to generate a first analysis of the first image data; identify a clinical finding in the first image data based on the first analysis; compare the first analysis to a second analysis, the second analysis generated from second image data obtained in a second image acquisition; and, when comparing identifies a change between the first analysis and the second analysis, trigger a notification at the imaging apparatus regarding the clinical finding to prompt a responsive action.

Abstract: Various methods and systems are provided for x-ray imaging. In one embodiment, a method for an image pasting examination comprises acquiring, via an optical camera and/or depth camera, image data of a subject, controlling an x-ray source and an x-ray detector according to the image data to acquire a plurality of x-ray images of the subject, and stitching the plurality of x-ray images into a single x-ray image. In this way, optimal exposure techniques may be used for individual acquisitions in an image pasting examination such that the optimal dose is utilized, stitching quality is improved, and registration failures are avoided.

Abstract: A system for imaging a subject is provided. The system includes a radiation source, a radiation detector, and a controller. The radiation source is operative to transmit electromagnetic rays through the subject. The radiation detector is operative to receive the electromagnetic rays after having passed through the subject so as to generate a plurality of projections of the subject. The controller is operative to display one or more selectively adjustable markers that define an image stack. The controller is further operative to reconstruct one or more images within the image stack based at least in part on the plurality of projections. Reconstruction of the one or more images is on demand.

Abstract: Apparatus, systems, and methods to capture and combine patient vitals and image data are disclosed. An example apparatus includes a video capturing device or an audio receiving device, a vitals data manager, and a vitals aggregator. The video capturing device captures visual vital information of a patient from a vital monitor during an imaging procedure. The audio receiving device captures audible vital information of the patient during the imaging procedure. The vitals data manager receives the captured visual vital information or the captured audible vital information, the captured visual vital information or the captured audible vital information to be tagged with an identifier of the patient to form tagged vitals information. The vitals aggregator receives the tagged vitals information and the image associated with the patient, the vitals aggregator to organize the tagged vitals information with the image associated with the patient to form a composite image.