Siemens Healthcare Gmbh

Chen Liu

Tommaso Mansi

Daphne Yu

Shun P Miao

Kaloian Petkov

Sandra Sudarsky

For three-dimensional rendering, a machine-learnt model is trained to generate representation vectors for rendered images formed with different rendering parameter settings. The distances between representation vectors of the images to a reference are used to select the rendered image and corresponding rendering parameters that provides a consistency with the reference. In an additional or different embodiment, optimized pseudo-random sequences are used for physically-based rendering. The random number generator seed is selected to improve the convergence speed of the renderer and to provide higher quality images, such as providing images more rapidly for training compared to using non-optimized seed selection.

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Vaud, Switzerland

Chen Liu