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Xi Fang (方 希) |
Howdy! My name is Xi Fang and I am a PhD student at the biomedical engineering department of Rensselaer Polytechnic Institute. Before coming to RPI, I obtained Bachelor’s degree in Information Security from the School of Computing at Wuhan University. During my undergraduate period, I conducted two internships and got accessed to lots of cutting-edge technologies and state-of-the-art theories relevant to medical imaging and image processing. I am now a research assistant in Deep Imaging Analysitc Lab.
Research Interest
I work in the field of medical image analysis, I focus on the following research topics:- Medical image segmentation
- Medical image registration
- Deep learning based surgical planning
- Point Cloud processing
Education
- 2018.08-Present Ph.D in Deep Imaging Analytics Lab, Rensselaer Polytechnic Institute. Supervisor: Prof. Pingkun Yan
- 2014.09-2018.06 B.S. in School of Computing, Wuhan University. Supervisor: Prof. Bo Du
Publications
Listed as first or co-first author:
[1] Xi Fang, Uwe Kruger, Fatemeh Homayounieh, Hanqing Chao, Jiajin Zhang, Subba R. Digumarthy, Chiara D. Arru, Mannudeep K. Kalra, Pingkun Yan, "Association of AI Quantified COVID-19 Chest CTand Patient Outcome," International Journal of Computer Assisted Radiology and Surgery (IJCARS), 2021. [Link]
[2] Hanqing Chao*, Xi Fang*, Jiajin Zhang*, Fatemeh Homayounieh, Chiara D. Arrub, Subba R. Digumarthyb, Rosa Babaeic, Hadi K. Mobinc, Iman Mohsenic, Luca Sabad, Alessandro Carrieroe, Zeno Falaschie, Alessio Paschee, Ge Wanga, Mannudeep K. Kalrab, Pingkun Yan, "Integrative analysis for COVID-19 patient outcome prediction," Medical Image Analysis (MedIA), 2021 (*Equal Contribution). [Link]
[3] Xi Fang, Pingkun Yan, “Multi-organ Segmentation over Partially Labeled Datasets with Multi-scale Feature Abstraction,” IEEE transaction on medical imaging (TMI), 2020. [Link]
[4] Xi Fang, Sheng Xu, Bradford J Wood, Pingkun Yan, “Deep learning-based liver segmentation for fusion-guided intervention,” International Journal of Computer Assisted Radiology and Surgery (IJCARS), 2020. [Link]
[5] Xi Fang, Bo Du, Sheng Xu, Bradford J Wood, Pingkun Yan, Vol. 11313. International Society for Optics andPhotonics, 2020. (Oral) “Unified Multi-scale Feature Abstraction for Medical Image Segmentation,” Medical Imaging: Image Processing, 2020. [Link]
[6] Xi Fang, Thomas Sanford, Baris Turkbey, Sheng Xu, Bradford J. Wood, and Pingkun Yan, "Division and Fusion: Rethink Convolutional Kernels for 3D Medical Image Segmentation," International Workshop on Machine Learning in Medical Imaging, 2020. [Link]
Listed as co-author:
[1] Zhao Peng, Jieping Zhou, Xi Fang, Pingkun Yan, Hongming Shan, Ge Wang, X. George Xu, Xi Pei, "Data Augmentation for Training Deep Neural Networks," Auto-Segmentation for Radiation Oncology, 2021 [Link]
[2] Zhao Peng, Xi Fang, Pingkun Yan, Hongming Shan, Tianyu Liu, Xi Pei, Ge Wang, Bob Liu, Mannudeep K Kalra, X George Xu, "A method of rapid quantification of patient‐specific organ doses for CT using deep‐learning‐based multi‐organ segmentation and GPU‐accelerated Monte Carlo dose computing," Medical Physics, 2020. [Link]
[3] Zengmao Wang, Xi Fang, Xinyao Tang, Chen Wu, "Multi-class active learning by integrating uncertainty and diversity," IEEE Access, 2018. [Link]
Projects
Deep learning based COVID-19 patient outcome prediction
Interface
(To be developed)
Services
Journal and Conference Reviewer:
- Medical Physics
- Neuro Computing
- CVPR
- MICCAI
Awards
- 2017, Meritorious Winner | Mathematical Contest In Modeling(MCM)