公开(公告)号：US20230071535A1

公开(公告)日：2023-03-09

申请号：US17470076

申请日：2021-09-09

申请人： GE Precision Healthcare LLC ,  University of Zurich

发明人： Sidharth Abrol ,  Bipul Das ,  Vanika Singhal ,  Amy Deubig ,  Sandeep Dutta ,  Daphné GERBAUD ,  Bianca Sintini ,  Ronny BÜCHEL ,  Philipp KAUFMANN

IPC分类号： G06T7/00 ,  G06T5/00 ,  G06T7/11 ,  G06N20/00 ,  G16H30/40 ,  G06K9/32

摘要： Systems/techniques that facilitate learning-based domain transformation for medical images are provided. In various embodiments, a system can access a medical image. In various aspects, the medical image can depict an anatomical structure according to a first medical scanning domain. In various instances, the system can generate, via execution of a machine learning model, a predicted image based on the medical image. In various aspects, the predicted image can depict the anatomical structure according to a second medical scanning domain that is different from the first medical scanning domain. In some cases, the first and second medical scanning domains can be first and second energy levels of a computed tomography (CT) scanning modality. In other cases, the first and second medical scanning domains can be first and second contrast phases of the CT scanning modality.