This page aims to merge information from my other pages into a single one and yet show more details of research projects / highlights:
∎
Liverpool page,
∎
Strathclyde page and ∎
Dec 18-19, 2024 Workshop Imaging and AI Algorithms
Professor Chen is an applied and computational mathematician. His interests are in developing and analysing new and novel algorithms for a range of scientific and engineering applications. He has collaborated with many UK industries on mathematical modelling problems. More than 10 of his previous 30 PhD students worked directly with industrial funding.
His current research centers on multimodal data integration and the development of advanced imaging analysis techniques for high-resolution image processing, with a primary focus on inverse problems. His distinctive expertise lies at the intersection of advanced mathematics, variational models, and deep learning, where he designs novel AI algorithms tailored to limited-data training scenarios -- a domain fraught with significant computational and practical challenges. To address these challenges, he employs a diverse array of mathematical tools, including variational frameworks, partial differential equations (PDEs), nonlinear optimization, iterative optimization solvers, and data-driven deep learning architectures.
A core pillar of his work is its application to medical imaging, particularly in tackling complex tasks such as segmentation of low-quality, low-contrast images and diffeomorphic co-registration, which leverages reversible mapping techniques to align multimodal medical data.
His research is deeply collaborative, involving active partnerships with clinicians, medical professionals, and industrialists to ensure practical relevance and translational impact.
Currently he holds an honorary position at Clatterbridge Cancer Centre (NHS) as a clinical consultant.
He is keen to promote and welcome collaborations with his group and his Department where applied maths and stats are very strong.
Prior to joining Strathclyde, he was the director of two multidisciplinary research centres (CMIT and LCMH) in the University of Liverpool. Some of his publications can be found from Google scholar,
where one sees that papers published in Nature Scientific Report (2022), CVPR (2023) and SIAM IMS (2024) are from his current collaborations on Maths and AI.
Current research focuses on three major challeges: i segmentation and ii registration of low quality and texture images, and iii AI algorithms for few shots or self-learning segmentation.
Publications may be found on UoL page and also
software
Extenally, he is a member of the EPSRC Strategic Advisory Team in Healthcare Tech theme and also a
member of Research Committee of Edinburgh Mathematical Society.
He serves on the
Editorial Boards of
Numerical Algorithms:
NuMA
International Journal of Computer Mathematics:
IJCM
Journal of Mathematical Research with Applications:
JMRA
Journal of Imaging:
JoI
Computational Mathematics and Computer Modeling
CMCMA
Highlights of New 2024 papers:
- IVC (2024): Image and Vision Computing, Volume 150, October 2024, 105192
"Ricci curvature based volumetric segmentation" by
Na Lei, Jisui Huang, Ke Chen et al.
⚫
CODE from here and PDF here
- SIIMS (2024): SIAM Journal on Imaging Sciences,
``Three-stage approach for 2D/3D diffeomorphic multi-modality image registration with textural control'', Ke Chen and Huan Han.
⚫
CODE from here
SIAM Journal on Image Sciences by Ke Chen and Huan Han (2024)
- MMS (2024):
SIAM Multiscale Modeling and Simulation, ``Multiscale approach for variational problem joint diffeomorphic image registration and intensity correction: theory and application'', Peng Chen, Ke Chen, Huan Han, and Daoping Zhang, accepted to appear.
⚫
CODE from here
- Physics in Medicine & Biology (2024)
Self-supervised dual-domain balanced dropblock-network for low-dose CT denoising, by Ran An, Ke Chen and Hongwei Li (2024).
from
https://iopscience.iop.org/article/10.1088/1361-6560/ad29ba
[PDF here
]
-
Applied Mathematical Modelling:
A bi-variant variational model for diffeomorphic image registration with relaxed Jacobian determinant constraints, by
Li, Y., Chen, K., Chen, C. & Zhang, J., 30 Jun 2024, Vol 130, p. 66-93 (download from ArXiv)
-
Computerized Medical Imaging and Graphics:
Time multiscale regularization for nonlinear image registration, by Lili Bao, Ke Chen, Dexing Kong, Shihui Ying, Tieyong Zeng,
Vol 112, March 2024, 102331. [Download local PDF]
- Optics Express :
DaISy: diffuser-aided sub-THz imaging system, by Shao-Hsuan Wu, Yiyao Zhang, Ke Chen, and Shang-Hua Yang,
Vol. 32, Issue 7, pp. 11092-11106 (2024), [Download local PDF]
-
Topology-preserving image registration with novel multi-dimensional Beltrami regularization from https://www.sciencedirect.com/science/article/pii/S0307904X23004407
-
A fractional-order image segmentation model with application to low-contrast and piecewise smooth images
from https://www.sciencedirect.com/science/article/pii/S0898122123004996
-
Applied Mathematical Modelling: Topology-preserving image registration with novel multi-dimensional Beltrami regularization,
by Chongfei Huang, Ke Chen, Meixiang Huang, Dexing Kong, Jing Yuan, Volume 125, Part B, January 2024, Pages 539-556.
[Download Publisher or local
PDF]
-
Computers & Mathematics with Applications,
A fractional-order image segmentation model with application to low-contrast and piecewise smooth images
by Junfeng Cao, Ke Chen, Huan Han, Volume 153, 1 January 2024, Pages 159-171,
[Download local PDF]