Siemens Healthineers Ag

Daniel Giese

Jens Wetzl

Seung Su Yoon

Elisabeth Preuhs

Marc Vornehm

Maria Monzon

Carola Fischer

A computer-implemented method for determining scar segmentation includes receiving a medical image of an object to be segmented acquired after an application of a low-dose of contrast agent and determining a scar segmentation mask by applying a trained artificial neural network to the medical image. The low-dose of the contrast agent includes less contrast-agent than a standard full-dose of the contrast agent.

Computer-implemented method for determining scar segmentation

The disclosure relates to techniques for determining a motion parameter of a heart. A subset of a sequence of cardiac MR images is applied as a first input to a first trained convolutional neural network configured to determine, as a first output, a probability distribution of at least 2 anatomical landmarks. The sequence of cardiac MR images is cropped and realigned based on the at least 2 anatomical landmarks to determine a reframed and aligned sequence of new cardiac MR images showing the same orientation of the heart. The reframed and aligned sequence of new cardiac MR images is applied to a second trained convolutional neural network configured to determine, as a second output, a further probability distribution of the at least 2 anatomical landmarks in each new MR image of the reframed and aligned sequence, the motion parameter of the heart is determined based on the second output.

Automatic determination of a motion parameter of the heart

Growing community of inventors

Erlangen, Germany

Daniel Giese