Abstract: Various methods and systems are provided for denoising images. In one example, a method includes obtaining an input image and a noise map representing noise in the input image, generating, from the noise map and based on a calibration factor, a strength map, entering the input image and the strength map as input to a denoising model trained to output a denoised image based on the input image and the strength map, and displaying and/or saving the denoised image output by the denoising model.

Abstract: Systems/techniques that facilitate improved neural network inferencing efficiency with fewer parameters are provided. In various embodiments, a system can access a medical image on which an artificial intelligence task is to be performed. In various aspects, the system can facilitate the artificial intelligence task by executing a neural network pipeline on the medical image, thereby yielding an artificial intelligence task output that corresponds to the medical image. In various instances, the neural network pipeline can include respective skip connections from the medical image, prior to any convolutions, to each convolutional layer in the neural network pipeline.

Abstract: Various methods and systems are provided for x-ray imaging. In one embodiment, a method comprises acquiring an image of a subject, generating, based on the image and a plurality of parameters, a noise modulation map comprising an estimated amount of noise in each pixel of the image, selectively reducing noise in the image based on the noise modulation map to generate a final image, and displaying the final image. In this way, the radiation dose during imaging may be reduced while maintaining or even improving image quality.

Abstract: Various methods and systems are provided for x-ray imaging. In one embodiment, a method comprises acquiring an image of a subject, generating, based on the image and a plurality of parameters, a noise modulation map comprising an estimated amount of noise in each pixel of the image, selectively reducing noise in the image based on the noise modulation map to generate a final image, and displaying the final image. In this way, the radiation dose during imaging may be reduced while maintaining or even improving image quality.