Education
medical image analysis
GPA 3.7/4.0
GPA 4.0/4.0
Experiences
- Proposed a simple yet effective method for semi-supervised domain-generalized medical image segmentation.
- Designed two innovative modules. One is the Fourier-transform-based data augmentation; another is the confidence-aware cross pseudo supervision.
- Wrote a paper which was submitted to AAAI 2022 as the first author.
- Won the second price in the this challenge.
- Proposed a new method combining CycleGAN and U-net to solve this problem.
- Designed a novel post-processing method called cutting and centre.
- Wrote a paper which was accepted by MICCAI 2021 workshop as the first author.
- Built the SlowFast networks to tackle this problem.
- Used Pseudo-Labeling method to deal with the insufficient labeled data.
- Won the second prize of the 13th SRTP(Student Research Training Program) of Shandong University.
- Learned basic concepts of deep learning.
- Studied deep learning library such as tensorflow and keras.
- Built the analysis model based on CNN.
Awards
Second Scholarship of Shandong University
- 2020
Second Scholarship of Shandong University
- 2019
Second Scholarship of Shandong University
- 2018
The second prize of the 13th SRTP(Student Research Training Program) of Shandong University
- 2018
Publications
Deep Generative Models, and Data Augmentation, Labelling, and Imperfections(MICCAI workshop), 2021.
Association for the Advancement of Artificial Intelligence(AAAI), 2022.