Abstract: Methods and systems are provided for diagnosing early stages of inflammatory bowel disease (IBD), IBD severity predictions, and the preventions of invasive cancers associated with IBD. Deep learning methods are used for accurate histologic assessment of IBD in one or more target patients. In aspects, IBD associated dysplasia and adenocarcinoma is detected from histopathology data. For example, a deep learning model is modified and trained using a training data set comprising histopathology images to enable Bayesian deep learning. In aspects, the training data set may be labeled based on genetic and immunologic factors. A target patient can be diagnosed as having IBD at a particular severity level based on an output by the deep learned model. Additionally, a care plan for the target patient may be determined, organized, or modified based on the output provided by the deep learned model.

Abstract: An automatic field-of-view (FOV) prescription system is provided. The system includes an FOV prescription computing device that includes at least one processor electrically coupled to at least one memory device. The at least one processor is programmed to receive localizer images that depict an anatomy, and generate masks associated with the localizer images, wherein the masks represent part of the localizer images that depict the anatomy. The at least one processor is also programmed to calculate bounding boxes surrounding the anatomy based on the masks, generate an FOV based on the bounding boxes, and output the FOV.

Abstract: Method (1000) and system (100) for image processing for a medical device is provided. The method (1000) includes acquiring (1010) a plurality of images of a subject using an image acquisition system (110) of the medical device. The method (1000) further includes identifying and differentiating (1020) a plurality of background pixels and a plurality of foreground pixels in the images using the deep learning module (125). The method (1000) further includes suppressing (1030) the identified background pixels using a mask and processing the foreground pixels for subsequent reconstruction and/or visualization tasks.

Abstract: An automatic field-of-view (FOV) prescription system is provided. The system includes an FOV prescription computing device that includes at least one processor electrically coupled to at least one memory device. The at least one processor is programmed to receive localizer images that depict an anatomy, and generate masks associated with the localizer images, wherein the masks represent part of the localizer images that depict the anatomy. The at least one processor is also programmed to calculate bounding boxes surrounding the anatomy based on the masks, generate an FOV based on the bounding boxes, and output the FOV.

Abstract: Methods and systems are provided for reducing background noise in magnetic resonance (MR) image and parametric map visualization using segmentation and intensity thresholding. An example method includes segmenting the MR image or parametric map into foreground which includes a region of anatomy of interest and background which is outside of the region of anatomy of interest, applying an intensity threshold to the background and not applying the intensity threshold to the foreground of the MR image or parametric map to produce a noise reduced MR image or noise reduced parametric map, and displaying the noise reduced MR image or noise reduced parametric map via a display device.

Abstract: Methods and systems are provided for reducing background noise in magnetic resonance (MR) image and parametric map visualization using segmentation and intensity thresholding. An example method includes segmenting the MR image or parametric map into foreground which includes a region of anatomy of interest and background which is outside of the region of anatomy of interest, applying an intensity threshold to the background and not applying the intensity threshold to the foreground of the MR image or parametric map to produce a noise reduced MR image or noise reduced parametric map, and displaying the noise reduced MR image or noise reduced parametric map via a display device.

Abstract: Several methods and a system for real time capture and communication of in-transit patient medical information are disclosed. In one embodiment, the system includes an instrument to capture a health data of a patient while the patient is in transit from a first location to a second location. The system also includes, an integration device having a processor and a memory coupled to the instrument and other instruments capturing the health data of the patient while the patient is in transit from the first location to the second location. In addition, the system includes a communication module of the integration device to transmit the health data to one or more of a client device, a dispatcher device, a hospital based device, a law enforcement device and an emergency personnel device while the patient is in transit from the first location to the second location.