Dr Jinming Duan BSc PhD

Dr Jinming Duan

School of Computer Science
Lecturer of Computer Science

Contact details

Address
The School of Computer Science
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Dr Jinming Duan is a Lecturer in Artificial Intelligence in Medicine. His work focuses on cutting-edge machine learning methods for cardiovascular imaging. His PhD thesis focused on modern variational and partial differential equation (PDE)-based methods, with applications to image processing and analysis. He is a lead collaborator of the EPSRC SmartHeart Programme at University of Birmingham. 

His research works have appeared across multiple application publications, including proceedings such as MICCAI, and journals such as Nature Machine Intelligence, IEEE Transactions on Medical Imaging, IEEE Transactions on Image Processing, etc. He regularly reviews more than 30 reputable journals.

For more information, please see Dr Jinming's Computer Science profile.

 

 

Biography

Before moving to University of Birmingham, he was a Research Associate jointly within Department of Computing and Institute of Clinical Sciences at Imperial College London. There, he has been working closely with Prof. Daniel Rueckert , and researching cutting-edge artificial intelligence methods for cardiovascular imaging. Prior to that, he studied his PhD in Computer Science at University of Nottingham. His PhD thesis focused on modern variational and partial differential equation (PDE)-based methods, with applications to image processing and analysis. He acquired both his undergraduate and master degrees in Computer Science.

 His research works have appeared across multiple application publications, including proceedings such as International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), and journals such as Nature Machine Intelligence, IEEE Transactions on Medical Imaging, IEEE Transactions on Image Processing, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Pattern Recognition, Physics in Medicine and Biology, Journal of Mathematical Imaging and Vision, Journal of Global Optimisation, etc. He regularly reviews more than 30 reputable journals.

Research

His research includes deep neural nets, variational methods, partial/ordinary differential equations, numerical optimisation, and finite difference/element methods, with applications to image processing, computer vision and medical imaging analysis.

Publications

Recent publications

Article

Lu, W, Duan, J, Orive Miguel, D, Herve, L & Styles, I 2019, 'Graph- and finite element-based total variation models for the inverse problem in diffuse optical tomography', Biomedical Optics Express, vol. 10, no. 6, pp. 2684-2707. https://doi.org/10.1364/BOE.10.002684

Spencer, J, Chen, K & Duan, J 2019, 'Parameter-free selective segmentation with convex variational methods', IEEE Transactions on Image Processing , vol. 28, no. 5, pp. 2163-2172. https://doi.org/10.1109/TIP.2018.2883521

Bello, GA, Dawes, TJW, Duan, J, Biffi, C, De Marvao, A, Howard, LSGE, Gibbs, JSR, Wilkins, MR, Cook, SA, Rueckert, D & O’regan, DP 2019, 'Deep-learning cardiac motion analysis for human survival prediction', Nature Machine Intelligence, vol. 1, no. 2, pp. 95-104. https://doi.org/10.1038/s42256-019-0019-2

Duan, J, Bello, G, Schlemper, J, Bai, W, Dawes, TJW, Biffi, C, de Marvao, A, Doumou, G, O'Regan, DP & Rueckert, D 2019, 'Automatic 3D bi-ventricular segmentation of cardiac images by a shape-refined multi-task deep learning approach', IEEE Transactions on Medical Imaging, vol. 38, no. 9, pp. 2151-2164. https://doi.org/10.1109/TMI.2019.2894322

Tan, L, Pan, Z, Liu, W, Duan, J, Wei, W & Wang, G 2018, 'Image segmentation with depth information via simplified variational level set formulation', Journal of Mathematical Imaging and Vision, vol. 60, no. 1, pp. 1–17. https://doi.org/10.1007/s10851-017-0735-3

Ding, Y, Pardon, MC, Agostini, A, Faas, H, Duan, J, Ward, WOC, Easton, F, Auer, D & Bai, L 2017, 'Novel methods for microglia segmentation, feature extraction, and classification', IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 14, no. 6, pp. 1366-1377. https://doi.org/10.1109/TCBB.2016.2591520

Duan, J, Tench, C, Gottlob, I, Proudlock, F & Bai, L 2017, 'Automated segmentation of retinal layers from optical coherence tomography images using geodesic distance', Pattern Recognition, vol. 72, pp. 158-175. https://doi.org/10.1016/j.patcog.2017.07.004

Duan, J, Ward, WOC, Sibbett, L, Pan, Z & Bai, L 2017, 'Introducing diffusion tensor to high order variational model for image reconstruction', Digital Signal Processing, vol. 69, pp. 323-336. https://doi.org/10.1016/j.dsp.2017.07.001

Yang, D, Subramanian, G, Duan, J, Gao, S, Bai, L, Chandramohanadas, R & Ai, Y 2017, 'A portable image-based cytometer for rapid malaria detection and quantification', PLoS ONE, vol. 12, no. 6, e0179161. https://doi.org/10.1371/journal.pone.0179161

Lu, W, Duan, J, Qiu, Z, Pan, Z, Liu, RW & Bai, L 2016, 'Implementation of high-order variational models made easy for image processing', Mathematical Methods in the Applied Sciences, vol. 39, no. 14, pp. 4208-4233. https://doi.org/10.1002/mma.3858

Duan, J, Lu, W, Pan, Z & Bai, L 2016, 'New second order Mumford-Shah model based on Γ-convergence approximation for image processing', Infrared Physics and Technology, vol. 76, pp. 641-647. https://doi.org/10.1016/j.infrared.2016.04.016

Duan, J, Qiu, Z, Lu, W, Wang, G, Pan, Z & Bai, L 2016, 'An edge-weighted second order variational model for image decomposition', Digital Signal Processing, vol. 49, pp. 162-181. https://doi.org/10.1016/j.dsp.2015.10.010

Conference contribution

Duan, J, Schlemper, J, Bai, W, Dawes, TJW, Bello, G, Biffi, C, Doumou, G, De Marvao, A, O’Regan, DP & Rueckert, D 2018, Combining deep learning and shape priors for bi-ventricular segmentation of volumetric cardiac magnetic resonance images. in H Lombaert, B Paniagua, B Egger, M Lüthi, M Reuter & C Wachinger (eds), Shape in Medical Imaging : nternational Workshop, ShapeMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11167 LNCS, Springer Verlag, pp. 258-267, International Workshop on Shape in Medical Imaging, ShapeMI 2018 held in conjunction with 21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018, Granada, Spain, 20/09/18. https://doi.org/10.1007/978-3-030-04747-4_24

Schlemper, J, Oktay, O, Bai, W, Castro, DC, Duan, J, Qin, C, Hajnal, JV & Rueckert, D 2018, Cardiac MR segmentation from undersampled k-space using deep latent representation learning. in JA Schnabel, C Davatzikos, C Alberola-López, G Fichtinger & AF Frangi (eds), Medical Image Computing and Computer Assisted Intervention – MICCAI 2018: 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part I. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11070 LNCS, Springer Verlag, pp. 259-267, 21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018, Granada, Spain, 16/09/18. https://doi.org/10.1007/978-3-030-00928-1_30

Duan, J, Schlemper, J, Bai, W, Dawes, TJW, Bello, G, Doumou, G, De Marvao, A, O’Regan, DP & Rueckert, D 2018, Deep Nested level sets: fully automated segmentation of cardiac MR images in patients with pulmonary hypertension. in AF Frangi, G Fichtinger, JA Schnabel, C Alberola-López & C Davatzikos (eds), Medical Image Computing and Computer Assisted Intervention – MICCAI 2018: 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part IV. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11073 LNCS, Springer Verlag, pp. 595-603, 21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018, Granada, Spain, 16/09/18. https://doi.org/10.1007/978-3-030-00937-3_68

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