Search Submissions ๐Ÿ”Ž

Results for "Xinlei Mi": 3 found

Artificial Intelligence Based Auto-Contouring for Organs at Risk in Head and Neck

Authors: Mylinh Dang, Laila A Gharzai, Xinlei Mi, Poonam Yadav

Affiliation: Northwestern Feinberg School of Medicine, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Northwestern Medicine

Abstract Preview: Purpose: Delineation of organs at risk (OAR) in the head/neck region requires substantial physician time. Many artificial intelligence (AI) based auto-contouring software are commercially available. T...

Enhancing the CT Contrast Via Attention-Gated Contrast Enhancement Gan (AGCE-GAN)

Authors: Nan Li, Yaoying Liu, Shouping Xu, Xinlei Xu, Gaolong Zhang

Affiliation: School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, School of physics, Beihang University, Beihang University, Department of Radiation Oncology

Abstract Preview: Purpose:
CT simulation is essential for radiation therapy preparation but has limitations in distinguishing lesions. Contrast-enhanced CT (CECT) improves lesion detection and characterization, but ...

Using Multiple Sequences MRI for Synthesizing CT Based on a Deep Learning Approach

Authors: Jie Hu, Nan Li, Chuanbin Xie, Shouping Xu, Xinlei Xu, Gaolong Zhang, Zhilei Zhang

Affiliation: School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Department of Radiation Oncology, the First Medical Center of the People's Liberation Army General Hospital, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, Peopleสผs Republic of China, Department of Radiation Oncology, School of Physics, Beihang University, Beijing, 102206, Peopleสผs Republic of China

Abstract Preview: Purpose: This study aims to synthesize CT images for MRI-only radiation therapy using a deep learning approach that integrates information from the T1- and T2-weighted MRI sequence.
Methods: 97 hea...