Reviewer
000-051-602
Xiaokun Liang
Assistant Professor Department: Radiation oncology Certificate Views : 564 Followers : 0| Name: | Xiaokun Liang |
| Designation: | Assistant Professor |
| Department: | Radiation oncology |
| Research Area: | Medical Image Analysis, X-ray CT Guided Radiation Therapy, Medical Physics, Deep learning |
| Organization: | Stanford University |
| Contact: | Contact Reviewer |
| About: | I am currently a Distinguished Research Fellow at SIAT. My research lies at the intersection of artificial intelligence and medical image analysis, with a primary focus on the medical image guided therapy. Specifically, we focus on: (1) Developing an unsupervised learning framework for real-time volumetric tumor guidance via cone-beam projection image; (2) Developing one-shot learning for CT deformable image registration with few training data; (3) Developing the data-driven based cone-beam CT artifact reduction algorithm. Before joining SIAT, I was a visiting student scholar at Stanford University, working with Prof. Lei Xing. I obtained my Ph.D. degree, University of Chinese Academy of Sciences (UCAS) in 2021; M.Sc degree, Guangdong Medical University in 2016; and B.Eng degree, Southern Medical University in 2013. |
| Status: |
Journal
| Author: | Liang, Xiaokun; Li, Na; Zhang, Zhicheng; Xiong, Jing; Zhou, Shoujun; Xie, Yaoqin |
| Title: | Incorporating the Hybrid Deformable Model for Improving the Performance of Abdominal CT Segmentation via Multi-Scale Feature Fusion Network |
| Publication Year: ISSN: Volume: Issue: |
2021 1361-8415 73 |
| Indexing: | SCOPUS, SCI-E, UGC-CARE, ABCD-Index, |
| Visit Paper: | Click here |
| More Details | Click here |
