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Abstract #3850

Feasibility study of Attention-Guided Pix2Pix GAN for the synthesizing of enhanced cerebral vascular images in 7 Tesla MRI

Jia Tan1, Zhiming Zhen2, Qiuli Wang2, Wei Chen3, Zihong Wang1, and Wei Chen2
1Department of Medical Engineering, First Affiliated Hospital of Army Medical University, Chongqing, China, 27T Magnetic Resonance Translational Medicine Research Center, Department of Radiology, Southwest Hospital, Army Medical University, Chongqing, China, 3MR Research Collaboration Team, Siemens Healthineers Ltd., Wuhan, China

Synopsis

Keywords: AI/ML Image Reconstruction, Blood vessels, 7T MRI; MRI synthesis; Contrast-enhanced T1WI

Motivation: The application of 7T contrast-enhanced (CE) MRI in cerebral vascular imaging offers superior spatial resolution, enabling enhanced visualization of intricate brain plaques. Nonetheless, the administration of contrast agents imposes a certain economic and health burden on patients.

Goal(s): To develop the Attention-Guided Pix2Pix GAN method for synthesizing 7T CE-T1WI images from 7T pre-contrast T1WI, aiming at evaluating cerebral vascular plaque.

Approach: The performance of synthetic 7T CE-T1WI image was compared to real 7T CE-T1WI image.

Results: Attention-Guided Pix2Pix GAN successfully synthesizes high-quality 7T CE-T1WI images from 7T pre-contrast T1WI data, which was comparable to real 7T CE-T1WI image.

Impact: The model we proposed can generate high-quality 7T magnetic resonance cerebrovascular enhancement images, which makes it possible to diagnose cerebral vessels without the use of contrast agents.

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Keywords