Abstract: A pulmonary artery flow restrictor system includes a funnel shaped membrane with a proximal base and a restrictive distal opening which is stretchable to larger sizes. A self-expanding frame is attached to the proximal base of the membrane for securing the membrane within the pulmonary artery.

Abstract: A perception system, comprising a set of reference sensors; a set of test sensors and a computing device, which is configured for receiving first training signals from the set of reference sensors and receiving second training signals from the set of test sensors, the set of reference sensors and the set of test sensors simultaneously exposed to a common scene; processing the first training signals to obtain reference images containing reference depth information associated with the scene; and using the second training signals and the reference images to train a neural network for transforming subsequent test signals from the set of test sensors into test images containing inferred depth information.

Abstract: A system and method for generating a high-density three-dimensional (3D) map are disclosed. The system comprises acquiring at least one high density image of a scene using at least one passive sensor; acquiring at least one new set of distance measurements of the scene using at least one active sensor; acquiring a previously generated 3D map of the scene comprising a previous set of distance measurements; merging the at least one new set of distance measurements with the previous set of upsampled distance measurements, wherein merging the at least one new set of distance measurements further includes accounting for a motion transformation between a previous high-density image frame and the acquired high density image and the acquired distance measurements; and overlaying the new set of distance measurements on the high-density image via an upsampling interpolation, creating an output 3D map.

Abstract: A system and method for generating a high-density three-dimensional (3D) map are disclosed. The system comprises acquiring at least one high density image of a scene using at least one passive sensor; acquiring at least one new set of distance measurements of the scene using at least one active sensor; acquiring a previously generated 3D map of the scene comprising a previous set of distance measurements; merging the at least one new set of distance measurements with the previous set of upsampled distance measurements, wherein merging the at least one new set of distance measurements further includes accounting for a motion transformation between a previous high-density image frame and the acquired high density image and the acquired distance measurements; and overlaying the new set of distance measurements on the high-density image via an upsampling interpolation, creating an output 3D map.

Abstract: System, apparatus, method, and computer readable media for edge-enhanced non-local means (NLM) image denoising. In embodiments, edge detail is preserved in filtered image data by weighting of the noisy input target pixel value with other pixel values based on self-similarity and further informed by a data-driven directional spatial filter. Embodiments herein may denoise regions of an image lacking edge characteristics with a more uniform spatial filter than those having edge characteristics. In embodiments, directionality of a spatial filter function is modulated based on an edge metric to increase the weighting of pixel values along an edge when there is a greater probability the edge passes through the target pixel. In further embodiments, the adaptive spatial filter is elliptical and oriented relative to a spatial gradient direction with non-uniform filter widths that are based on the edge metric.

Abstract: System, apparatus, method, and computer readable media for edge-enhanced non-local means (NLM) image denoising. In embodiments, edge detail is preserved in filtered image data by weighting of the noisy input target pixel value with other pixel values based on self-similarity and further informed by a data-driven directional spatial filter. Embodiments herein may denoise regions of an image lacking edge characteristics with a more uniform spatial filter than those having edge characteristics. In embodiments, directionality of a spatial filter function is modulated based on an edge metric to increase the weighting of pixel values along an edge when there is a greater probability the edge passes through the target pixel. In further embodiments, the adaptive spatial filter is elliptical and oriented relative to a spatial gradient direction with non-uniform filter widths that are based on the edge metric.