DisAsymNet: Disentanglement of Asymmetrical Abnormality on Bilateral Mammograms Using Self-adversarial Learning
Published in MICCAI, 2023
Recommended citation: Wang, X., Tan, T., Gao, Y. et al. (2023). "DisAsymNet: Disentanglement of Asymmetrical Abnormality on Bilateral Mammograms Using Self-adversarial Learning." MICCAI. https://doi.org/10.1007/978-3-031-43990-2_6
We propose a novel framework, DisAsymNet, which utilizes asymmetrical abnormality transformer guided self-adversarial learning for disentangling abnormalities and symmetric Bi-MG.
Recommended citation: Wang, X., Tan, T., Gao, Y. et al. (2023). “DisAsymNet: Disentanglement of Asymmetrical Abnormality on Bilateral Mammograms Using Self-adversarial Learning” MICCAI.