Bibo Shi, Ph.D
Research Assosicate
Carl E. Ravin Advanced Imaging Laboratories (RAI Labs)
Duke University Medical Center
✉: bibo (dot) shi (at) duke (dot) edu
☎: (919) 681-3026
Last Update: May, 2017
About Me
I am a Research Associate at Duke University, working with Dr. Joseph Lo in Carl E. Ravin Advanced Imaging Laboratories (RAI Labs). My research centered around Machine Learning, Deep Learning and their applications in Medical Image Analysis, Computer Vision, and their intersection.
I received my Ph.D. degree in Computer Science and M.S. degree in Biomedical Engineering (BME) from Ohio University in 2015 and 2011, my B.S. in BME from HUST, China, in 2008.
In April 2017, our team BlueLived ranked No.13 during the 3rd round of the Digital Mammography DREAM Challenge.
In Mar. 2017, our paper was accpeted to Academic Radiology.
In Mar. 2017, our team BlueLived ranked No.19 during the 2nd round of the Digital Mammography DREAM Challenge.
In Jan. 2017, our team BlueLived ranked No.6 during the 1st round of the Digital Mammography DREAM Challenge, which has over 1000 participants and 100 teams.
In Dec. 2016, our paper won the best paper award in ICMLA'16 conference.
In June 2016, I got selected for the CVPR 2016 Doctoral Consortium and awarded a travel grant.
In Mar. 2016, I started work as a research associate in RAI labs at Duke University!
In Dec. 2015, I graduated from Ohio University with Ph.D. degree in Computer Science!
Research Interests
-   Machine learning
-   Medical image analysis
-   Deep learning
-   Computer vision
-   Pattern recognition
Publications
  Journals
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Can occult invasive disease in ductal carcinoma in situ be predicted using computer-extracted mammographic features?
Bibo Shi, Lars Grimm, Maciej A. Mazurowski, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, E. Shelley Hwang, Joseph Y. Lo
Academic Radiology, 2017
[ Link ] -
Nonlinear Feature Transformation and Deep Fusion for Alzheimer's Disease Staging Analysis
Bibo Shi, Yani Chen, Charles D. Smith, and Jundong Liu
Pattern Recognition, 2017
[ Link | PDF | BibTex ] -
Multi-scale Based Image Enhancement Algorithm for Hepatic Portal Vein with Multi-slice Spiral CT Angiography
Liu Jingjing, Zhang Zhi,Shi Bibo,Song Enmin, Xie Qingguo, Hu Daoyu, Li Zhen, Hu Xuemei.
Journal of Image and Graphics (China), 2008
[ Link | BibTex]
  Conferences
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Hippocampus Segmentation through Multi-View Ensemble Convnets
Yani Chen, Bibo Shi, Zhewei Wang, Pin Zhang, Charles Smith, Jundong Liu
IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), 2017
[ PDF | BibTex] -
Prediction of occult invasive disease in ductal carcinoma in situ using computer-extracted mammographic features
Bibo Shi, Lars Grimm, Maciej A. Mazurowski, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, E. Shelley Hwang, Joseph Y. Lo
SPIE Medical Imaging (SPIE MI'17), 2017
[ Link ] -
Can upstaging of ductal carcinoma in situ be predicted at biopsy by histologic and mammographic features?
Bibo Shi, Lars Grimm, Maciej A. Mazurowski, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, E. Shelley Hwang, Joseph Y. Lo
SPIE Medical Imaging (SPIE MI'17), 2017
[ Link ] -
Nonlinear Metric Learning for Semi-Supervised Learning via Coherent Point Drifting
Pin Zhang, Bibo Shi, Charles Smith, Jundong Liu
IEEE 15th International Conference on Machine Learning and Application (ICMLA 2016), 2016 (best paper award)
[PDF | Link | BibTex] -
Quad-mesh Based Radial Distance Biomarkers for Alzheimer's Disease
Kevin Hobbs, Pin Zhang, Bibo Shi, Charles D. Smith, and Jundong Liu
IEEE 13th International Symposium on Biomedical Imaging (ISBI 2016), 2016
[ PDF | BibTex] -
Nonlinear Feature Transformation and Deep Fusion for Alzheimer's Disease Staging Analysis
Yani Chen, Bibo Shi, Charles D. Smith, and Jundong Liu
MICCAI 2015 - Workshop on Machine Learning in Medical Imaging, 2015.(MICCAI-MLMI2015), 2015
[ PDF | BibTex] -
Nonlinear Metric Learning for Alzheimer's Disease Diagnosis with Integration of Longitudinal Neuroimaging Features
Bibo Shi, Yani Chen, Kevin Hobbs, Charles D. Smith, and Jundong Liu
Proceedings of the 26th British Machine Vision Conference (BMVC'15), 2015
[ PDF | BibTex] -
Image Registration for Motion Estimation in Cardiac CT
Bibo Shi, Gene Katsevich, Be-Shan Chiang, Alexander Katsevich, and Alexander Zamyatin
SPIE Medical Imaging (SPIE MI'14), 2014
[ PDF] -
A Combined Local and Global Motion Estimation and Compensation Method for Cardiac CT
Qiulin Tang, Beshan Chiang, Akinola Akinyemi, Alexander Zamyatin, Bibo Shi, and Satoru Nakanishi
SPIE Medical Imaging (SPIE MI'14), 2014
[ Link] -
Adaptive Multi-scale Total Variation Minimization Filter for Low Dose CT Imaging
Alexander Zamyatin, Gene Katsevich, Roman Krylov, Bibo Shi, and Zhi Yang
SPIE Medical Imaging (SPIE MI'14), 2014
[ PDF] -
Distance-informed Metric Learning for Alzheimer’s Disease Staging
Bibo Shi, Zhewei Wang, and Jundong Liu
36th Annual International Conference of the IEEE In Engineering in Medicine and Biology Society (EMBC'14), 2014
[ PDF | BibTex] -
Robust Separation of Visceral and Subcutaneous Adipose Tissues in Micro-CT of Mice
Bibo Shi, Shuisheng Xie, Darlene Berryman, Ed List, and Jundong Liu
35th Annual International Conference of the IEEE In Engineering in Medicine and Biology Society (EMBC'13), 2013
[ PDF | BibTex] -
Regularity-guaranteed Transformation Estimation in Medical Image Registration
Bibo Shi and Jundong Liu
SPIE Medical Imaging (SPIE MI'12), 2012
[ Link] -
Non-twist Regularization for Deformation Estimation
Bibo Shi and Jundong Liu
15th Annual Conference in Medical Image Understanding and Analysis (MIUA'11), 2011
[ PDF | BibTex]
  Manuscript in Preparation & Preprints
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Nonlinear Metric Learning for kNN and SVMs through Geometric Transformations
Bibo Shi and Jundong Liu
[ short version preprint PDF | BibTex] -
A Diffeomorphic Take for Nonlinear Metric Learning
Bibo Shi and Jundong Liu
[ PDF | BibTex]
Professional Activities
-   Referee:  IEEE Transactions on Image Processing, IEEE Transactions on Computational Biology and Bioinformatics, Multimedia Systems, Journal of Digital Imaging, MICCAI2017
-   Volunteer:  6th Great Lakes Bioinformatics Conference, 2011