Contrast-enhanced MRI synthesis from non-contrast MRI using attention CycleGAN

Tonghe Wang; Yang Lei; Walter J. Curran; Tian Liu; Xiaofeng Yang

doi:10.1117/12.2581064

15 February 2021 Contrast-enhanced MRI synthesis from non-contrast MRI using attention CycleGAN

Tonghe Wang, Yang Lei, Walter J. Curran, Tian Liu, Xiaofeng Yang

Proceedings Volume 11600, Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging; 116001L (2021) https://doi.org/10.1117/12.2581064
Event: SPIE Medical Imaging, 2021, Online Only

Conference Poster

Abstract

We propose a learning-based method to synthesize contrast-enhanced MR from non-contrast MR images. Attention network is integrated into a cycle-consistent adversarial network (CycleGAN) framework, called Atten-CycleGAN, to learn a mapping between non-contrast MRI and contrast MRI. Attentional U-Net was used as generator of CycleGAN to force the trained model to extract informative that can represent the specific difference between non-contrast MRI and contrast MRI, namely, the tissue contrast difference. To evaluate the proposed method, we retrospectively investigate 274 brain MR datasets. Each dataset contains a contrast-enhanced MR volume and a non-contrast MR volume. The contrast-enhanced one was served as ground truth and training target, and the non-contrast MR is the input. The proposed method was trained from 224 patients and evaluated by a hold-out test strategy on 50 patients. The average normalized mean absolute error of the synthesized contrast MR is 0.035±0.004. The proposed method has great potential in accurately generating contrast MR and therefore bypassing the contrast administration step during MR scan.

Citation Download Citation

Tonghe Wang, Yang Lei, Walter J. Curran, Tian Liu, and Xiaofeng Yang "Contrast-enhanced MRI synthesis from non-contrast MRI using attention CycleGAN", Proc. SPIE 11600, Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging, 116001L (15 February 2021); https://doi.org/10.1117/12.2581064

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