PROJECT DETAILS
Project Title
Reconstruction and Visualization of Neuron Structures of the Brain
Project Summary
Brain Research has recently received a lot of attention; examples include the heavily funded EU flagship project
Human Brain Project (HBP) and US Brain Research through Advancing Innovative Neuro-technologies (BRAIN)
Initiative. These two ambitious projects hope to advance our understanding of both normal and pathological brain
functions; offering potentially enormous benefits to society. One should also recognize that neuroscience is
generating exponentially growing volumes of imaging data from both healthy and diseased brains in animals and
humans. This enormous quantity of data, however, has created a number of substantial bottleneck issues for the
ambitious neurological projects, both in data processing and in need of heavy manual intervention. The lack of
powerful and effective computational tools for automatic segmentation and registration of neuron structures has
emerged as a major technical obstacle in Brain Research.
The aim of this project is to develop novel neuron registration algorithms and tools towards the goal of automatic
production of 3D digital atlas of nervous system for animals.
Academic Impact
Vaa3D system has been used extensively in neuroscience community. By using the Vaa3D system as a vehicle, the
research output, toolkit of automated neuronal segmentation and registration, will be employed directly in the
implementation of 3D digital atlases of nervous systems, pushing the UK to the frontier of Brain Research. The
delivery of GPU-based Vaa3D system will vastly speed up data processing and further boost neuroscience and
medicine communities to develop new treatments for brain disorders, e.g. Parkinson’s and Alzheimer’s Diseases.
Societal Impact
This research will catalyze large-scale collaboration and data sharing, reconstruction of the brain at different
biological scales, federated analysis of clinical data to map diseases of the brain, and the development of braininspired computing systems. Through the delivery of GPU based parallel visualization platform (GPU-based
Vaa3D), scientists, clinicians, and engineers will be able to perform diverse experiments and share knowledge with
a common goal of unlocking the most complex structure in the world. With an unprecedented cross-disciplinary
scope, the ambitious projects, EU HBP and US BRAIN, are seeking to integrate neuroscience, computing and
medicine, unify brain research, and benefit the global scientific community. Our research will be unceasingly
upgraded by the advance of high performance computing techniques. The development and use of high
performance computing over the HBP and BRAIN's lifetime will pave the way for the human ultimate goal,
simulation of the whole human brain.
Training Opportunities
The training programme will be directed by Dr H. Yu, with co-supervision provided by Dr H. Peng. The training
programme will concentrate on facilitating the delivery of the four primary objectives:
(1) Computer visualization and graphics methodology. Dr H. Yu also runs a series of advanced seminars on
PhD Project Description
March 2016
geometry modelling, 3D reconstruction, visualization and rendering;
(2) Software development. Dr H. Peng and Dr H. Yu will provide hands-on training in the use of Vaa3D system and
medical volume data;
(3) Placement with leading research group and industry partner. Dr H. Peng’s group will provide the world leading
research placement—Allen Institute for Brain Science (USA);
(4) Communication skills, including the preparation of oral/poster symposium communications and peer-reviewed
publications; delivery will be through attendance of BU's extensive training course for new researchers and through
active participation in BU internal seminars and external formal/informal research activities outside BU.
SUPERVISORY TEAM
First Supervisor
Dr Hongchuan Yu, BU
Additional Supervisors
Dr Hanchuan Peng, Allen Institute for Brain Science, USA
Recent publications by
supervisors relevant to this
project
Dr Hongchuan Yu’s publications
(1) Hongchuan Yu, Yipeng Qin, Jian J. Zhang, Eigenface based surface
completeness, J. of Electronic Imaging, 24(2), 2015
(2) Hongchuan Yu, Jian J. Zhang, Tong-Yee Lee: Foldover-free shape
deformation for biomedicine. J. of Biomedical Informatics, 48:137-147, 2014
(3) Hongchuan Yu, Jian J. Zhang, Zheng Jiao, Geodesics on Point Clouds,
Mathematical Problems in Engineering, Vol.2014, ArticleID 860136, 2014
(4) Hongchuan Yu, Tong-Yee Lee, I-Cheng Yeh, Xiaosong Yang, Wenxi Li, Jian
J. Zhang: An RBF-Based Reparameterization Method for Constrained Texture
Mapping. IEEE Trans. on Vis. and Comp. Grap. 18(7):1115-1124, 2012
(5) Hongchuan Yu, Jian J. Zhang: Topology preserved shape deformation. The
Visual Computer 28(6-8):849-858, 2012
(6) Hongchuan Yu, Jian J. Zhang: Tensor-Based Feature Representation with
Application to Multimodal Face Recognition. Int'l J. of Pattern Recognition and
Artificial Intelligence, 25(8):1197-1217, 2011
(7) Hongchuan Yu, Mohammed Bennamoun, Chin-Seng Chua: An extension of
min/max flow framework. Image and Vision Computing Journal, 27(4):342-353,
2009
Dr Hanchuan Peng’s publications
(1) Peng, H., Hawrylycz, M., Roskams, J., Hill, S., Spruston, N., Meijering, E.,
Ascoli, G.A, BigNeuron: large-scale 3D neuron reconstruction from optical
microscopy images, Neuron, 87(2):252-256, 2015.
(2) Peng, H., Tang, J., Xiao, H., Bria, A., et al., Virtual finger boosts threedimensional imaging and microsurgery as well as terabyte volume image
visualization and analysis, Nature Communications, 5:4342, 2014.
(3) Peng, H., Bria, A., Zhou, Z., Iannello, G., and Long, F., Extensible
visualization and analysis for multidimensional images using Vaa3D, Nature
Protocols, 9(1):193-208, 2014.
(4) Peng, H., Chung, P., Long, F., Qu, L., Jenett, A., Seeds, A., Myers, E.W.,
and Simpson, J.H., BrainAligner: 3D registration atlases of Drosophila brains,
Nature Methods, 8(6):493-498, 2011.
(5) Peng, H., Ruan, Z., Long, F., Simpson, J.H., and Myers, E.W., V3D enables
PhD Project Description
March 2016
real-time 3D visualization and quantitative analysis of large-scale biological
image data sets, Nature Biotechnology, 28(4,):348-353, 2010.
INFORMAL ENQUIRIES
To discuss this opportunity further, please contact Dr Hongchuan Yu via email: [email protected]
ELIGBILITY CRITERIA
All candidates must satisfy the University’s minimum doctoral entry criteria for studentships of an honours degree at
Upper Second Class (2:1) and/or an appropriate Masters degree. An IELTS (Academic) score of 6.5 minimum (or
equivalent) is essential for candidates for whom English is not their first language.
Additional Eligibility
As there is a requirement that the successful applicant undertakes work placements in the Matched funder’s
company (Canada) for more than 18 months during the PhD program, applicants will be required to show that they
are willing and able to do this.
HOW TO APPLY
Please complete the online application form by 01/06/2016. Further information on the application process can be
found at: www.bournemouth.ac.uk/studentships
PhD Project Description
March 2016