Dr Yu Sun PhD

Dr Yu Sun

Institute of Cancer and Genomic Sciences
Honorary Senior Research Fellow, Associated Professor

Contact details

Address
Children's Brain Tumour Research Team
Institute of Child Health
Birmingham Women's and Children's NHS Foundation Trust
Steelhouse Lane
Birmingham
B4 6NH

Dr Yu Sun is an Honorary Senior Research Fellow in the Children's Brain Tumour Research Team in the Institute of Cancer and Genomic Sciences at the University of Birmingham and based at the Birmingham Women’s and  Children’s Hospital. She is also an Associated Professor at Southeast University in China, leading a MR Imaging and Brain Science research group in the Biological Science and Medical Engineering School. Southeast University is one of the national key universities administered directly under the Central Government and the Ministry of Education of China.

 Dr Yu Sun’s research focusses on the development of novel MR Imaging techniques for understanding, diagnosis and management of childhood tumour and neurological diseases. Currently, she has expended her research to apply the Multimodal functional imaging to the brain science including the following key research fields:

(1) Neural Circuit Mechanisms of Cognition

(2) Early Diagnosis and Intervention of Brain Disorders

(3) Brain-Inspired Computation and AI. 

Qualifications

  • PhD in Electronic, Electrical and Computer Engineering, University of Birmingham, U.K., 2009
  • MA in Computer Art, Southeast University, China, 1999
  • BSc in Biomedical Engineering, Southeast University China, 1997

Biography

Dr. Yu Sun studied initially at Southeast University in China gaining her Bachelor degree in Biomedical Engineering in 1997 and her Master degree in Computer Art in 1999. In 2000, she was awarded the Overseas Student Scholarship by the U.K. Government and started her Ph.D. in the school of Electronic, Electrical and Computer Engineering at University of Birmingham, U.K.

In 2006, she started her research career as a Research Fellow, upon the completion of her PhD, at the Children's Brain Tumour Research Team, which was led by Professor Andrew Peet. Since then she has worked on several European international projects and U.K projects including the EU framework 6 projects eTumour, HealthAgents and U.K. CCLG projects. Her research focussed on medical imaging processing and visualization, biomedical signal processing, image guided therapy, MRI and MRS based database and decision support system design for childhood brain tumours. During that time, she worked in close collaboration with European and U.K.’s universities, hospitals and industry to extend these techniques and obtained international working experience.

Since 2010, she had started to introduce the MRS technology to China and set up collaborations with Southeast University and Nanjing Drum Tower Hospital. After she was appointed as the Associated Professor in Biological Science and Medical Engineering School at Southeast University, she set up a research team focusing on the advance MR and MRS application in brain tumour and Alzheimer Disease (AD). She aims to make MR and MRS techniques widely and has had leadership roles in several multi-centre collaborations. In 2013, she was awarded as the Nanjing High-technology Talents by the Nanjing City Council in China.

Currently, Dr Yu Sun is working with Professor Andrew Peet to build up an international Imaging and Brain Science research team. This research team will focus on the cutting-edge research of the advanced MR imaging technology in biomedical and brain science, and finally, the innovative research results can be widely used in the early development of childhood health and education, brain disease prevention and detection, clinical diagnosis, quality control and assessment.

Teaching

Lecturer on Medical Imaging on MSc module.

Postgraduate supervision

PhD Students Main Supervisor -

  • 1 completed

PhD Students Co-Supervisor -

  • 1 completed, 2 in process

Research

Dr Yu Sun’s current research includes the following projects:

(1)  The clinical application of advanced MR and MRS techniques in paediatric brain oncology and neurological disease.

(2)  MRI imaging methodology for Moyamoya Disease.

(3)  The study of applications of multi-modal MRI techniques for olfactory nerve circuit and function in cognitive impairment disease.

(4)  Development, implementation and evaluation of a Multi-centre decision support system based on image big data and machine learning.

(5)  Development and implementation of an Image-guided Robotic surgery system for accurate treatment: A Multi-positional and multi-functional MRI-guided robotic surgery system.

Publications

Yu Sun, Yafei Wang, Jiaming Lu, Rengyuan Liu, Christopher Schwarz, Hui Zhao, Yue Zhang, Lingyi Xu, Suiren Wan, Bin Zhu, Bing Liu, Bing Zhang, Disrupted Functional Connectivity between Perirhinal and Parahippocampal Cortices with Hippocampal Subfields in Patients with Mild Cognitive Impairment and Alzheimer's Disease, Accepted by Oncotarget, 2017

Jisu Hu, Wenbo Wu, Bin Zhu, Suiren Wan*, Yu Sun*, Bing Zhang*, et al., (2016), Cerebral Glioma Grading Using Bayesian Network with Features Extracted from Multiple Modalities of Magnetic Resonance Imaging, PLOS ONE, 11(4): e0153369. DOI: 10.1371/journal.pone.0153369.

Hao J, Zou X, Wilson M, Davies NP, Sun Y, Peet AC, Arvanitis TN, (2012), A hybrid method of application of independent component analysis to in vivo 1H MR spectra of childhood brain tumours, NMR Biomed, Apr;25(4):594-606. doi: 10.1002/nbm.1776.

Davison JE, Davies NP, Wilson M, Sun Y, Chakrapani A, McKiernan PJ, Walter JH, Gissen P, Peet AC, (2011), MR spectroscopy-based brain metabolite profiling in propionic acidaemia: metabolic changes in the basal ganglia during acute decompensation and effect of liver transplantation, Orphanet J Rare Dis. May 9;6:19. doi: 10.1186/1750-1172-6-19.

Yu Sun, Nigel P. Davies, Kal Natarajan, Theodoros N. Arvanitis and Andrew C. Peet, (2010), Localisation, registration and visualisation of MRS volumes of interest on MR images, XII Mediterranean Conference on Medical and Biological Engineering and Computing, Springer Berlin Heidelberg, DOI:10.1007/978-3-642-13039-7_64.