Quantitative Analysis of Molecular Transport in the Extracellular Space Using Physics-Informed Neural Network

no code implementations • 23 Jan 2024 • Jiayi Xie, Hongfeng Li, Jin Cheng, Qingrui Cai, Hanbo Tan, Lingyun Zu, Xiaobo Qu, Hongbin Han

Consequently, the proposed method allows for the quantitative analysis and identification of the specific pattern of molecular transport within the ECS through the calculation of the Peclet number.

Content-Noise Complementary Learning for Medical Image Denoising

2 code implementations • IEEE Transactions on Medical Imaging 2022 • Mufeng Geng, Xiangxi Meng, Jiangyuan Yu, Lei Zhu, Lujia Jin, Zhe Jiang, Bin Qiu, Hui Li, Hanjing Kong, Jianmin Yuan, Kun Yang, Hongming Shan, Hongbin Han, Zhi Yang, Qiushi Ren, Yanye Lu

In this study, we propose a simple yet effective strategy, the content-noise complementary learning (CNCL) strategy, in which two deep learning predictors are used to learn the respective content and noise of the image dataset complementarily.

Generative Adversarial Network Image Denoising +1