Imperial College London

DrWenjiaBai

Faculty of MedicineDepartment of Brain Sciences

Lecturer in Artificial Intelligence in Medicine
 
 
 
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Contact

 

+44 (0)20 7594 8291w.bai Website

 
 
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Location

 

Data Science InstituteWilliam Penney LaboratorySouth Kensington Campus

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Summary

 

Summary

I am a lecturer jointly at Data Science Institute and Department of Brain Sciences, Imperial College London. I am also affiliated with Biomedical Image Analysis Group, Department of Computing.

My research is at the interface between machine learning and medical imaging. I am interested in medical image segmentation, registration, reconstruction, classification and prediction problems, as well as their translation to clinical research and healthcare. I feel fortunate to work with colleagues that span the spectrum from computing to medicine.

Previously, I completed my D.Phil in Engineering Science at University of Oxford and my M.Eng and B.Eng in Automation at Tsinghua University.

Please visit my personal website for more information.

Publications

Journals

Meyer H, Dawes T, Serrani M, et al., Genetic and functional insights into the fractal structure of the heart, Nature, ISSN:0028-0836

Chen C, Bai W, Davies R, et al., Improving the generalizability of convolutional neural network-based segmentation on CMR images, Frontiers in Cardiovascular Medicine, ISSN:2297-055X

Bhuva AN, Treibel TA, De Marvao A, et al., 2020, Sex and regional differences inmyocardial plasticity in aortic stenosis are revealed by 3D modelmachine learning, European Heart Journal-cardiovascular Imaging, Vol:21, ISSN:2047-2404, Pages:417-427

Chen C, Qin C, Qiu H, et al., 2020, Deep learning for cardiac image segmentation: A review, Frontiers in Cardiovascular Medicine, Vol:7, ISSN:2297-055X, Pages:1-33

Ruijsink B, Puyol-Antón E, Oksuz I, et al., 2020, Fully automated, quality-controlled cardiac analysis from CMR: Validation and large-scale application to characterize cardiac function, Jacc: Cardiovascular Imaging, Vol:13, ISSN:1876-7591, Pages:684-695

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