Abstract: A mechanism for generating a partially denoised image. A residual noise image, obtained by processing an image using a convolutional neural network, is weighted. The blending or combination of the weighted residual noise image and the (original) image generates the partially denoised image.

Abstract: One embodiment of the present disclosure may provide a method for training and tuning a neural network model, including: adding simulated noise to an initial image of an object to generate a noisy image (601, 603), the simulated noise taking the same form as natural noise in the initial image; training a neural network model on the noisy image using the initial image as ground truth (605), wherein in the neural network model is trained on the noisy work model a tuning variable is extracted or generated, the tuning variable defining an amount of noise removed during use (607); identifying a first value for the tuning variable that minimizes a training cost function for the tuning variable is identified or for the initial image; and assigning a second value for the tuning variable (611), the second value different than the first value, wherein the neural network model identifies more noise in the noisy image when using the second value than when using the first value.

Abstract: System and related methods for de-noising 3D imagery. The system (IPS) comprises a pre-trained discriminative neural network (NN). The network includes a sequence of 3D convolutional operators (CV) for processing a received 3D image volume into a 3D output image. The 3D output image has a lower noise level than the 3D input image.

Abstract: An imaging system (IS), comprising an image acquisition unit (AQ) for acquisition of image data (I1) of an object (OB). The image acquisition is based on an imaging signal imitable by the unit (AQ) to interact with the object. The image acquisition unit (AQ) is adjustable to operate at different acquisition parameters that determine a property of the imaging signal. A predictor component (PC) predicts, based at least on the acquired image data (I1), one or more properties of the object. An acquisition parameter adjuster (PA) adjusts, based on the predicted object properties, the acquisition parameter at which the image acquisition unit (AQ) is to acquire follow-up image data (I2).

Abstract: An imaging system (MIS), optionally a medical imaging system, with wireless communication capability and related method. The imaging system comprises a gantry (RG) rotatable around a rotation axis. The gantry includes a detector device (D) capable of recording, in plural spatial positions, measurement data in relation to a subject (such as a patient) (PAT) to be imaged. The system also includes a radio transmitter (TX) for generating a directed radio beam propagatable along a propagation axis to transmit the measurement data to a radio receiver (RX). The radio transmitter (TX) is arranged at the rotatable gantry and is operable so that the propagation direction intersects the rotation axis in a location that is situated away from the rotatable gantry.