The Medical Imaging Lab
From light physics to clinical translation — we build optical imaging methods that make non-invasive tissue monitoring possible.
Our Research Meet the TeamWhat We Do
Optical Instrumentation
We design and build purpose-driven optical systems for diffuse optical tomography, fluorescence imaging, and diffuse correlation spectroscopy. Explore →Light Transport Modelling
We develop analytical and numerical models for photon propagation in tissue — including NIRFAST, our open-source FEM-based forward modelling tool. Explore →Neuroimaging & Data Analysis
We build statistical, causal, and machine-learning methods for fNIRS data analysis, brain connectivity, and image reconstruction. Explore →100+
Peer-reviewed publications
4
Active Funded Projects
10+
Collaborating Institutions
25+
Years of Research
Featured Work
⭐ Highlighted Publication · Journal of Biomedical Optics
NIRFASTerFF: An accessible, cross-platform Python package for fast photon modeling
The NIRFASTerFF package provides a fast and license-free tool for photon modeling and can further streamline Python-based data processing in diffuse optical imaging, benefiting the biophotonics community. Read Paper →Latest News
- MI Lab Celebrates Seven Accepted Abstracts at fNIRS 2026 September 1, 2026
- MI Lab Faculty to Deliver Mini Courses at fNIRS 2026 in Macau September 1, 2026
- Illuminating Minds: Outreach Day for Future University Students August 12, 2026
- Computer Science and Optical Neuroimaging June 27, 2026
Recent Publications
- Overprocessing in neuroimaging processing pipelines, illustrated with functional near-infrared spectroscopy (fNIRS)’ Journal of Ambient Intelligence and Humanized Computing, 17(3), pp. 807–827 → Link
- Musculoskeletal and physiological responses to vortex wave stimulation in older adults’ The Journal of Physiology → Link
- Full Model Optimisation of the Processing Pipeline in Functional Near-Infrared Spectroscopy’ Neuroinformatics, 24(2), article 20. → Link
Open Opportunities
Unraveling Brain Complexity with fNIRS and Modelling Approaches
Self-Funded PhD Students Only
This project aims to develop computational, mathematical, and machine-learning methods to analyse fNIRS data and better characterise brain function and neuroplasticity. It will focus on improving signal quality, spatial resolution, and pattern detection for neuroscience and clinical research.fNIRS Neuroimaging Data Analysis of Surgical Neuroergonomics
Competition Funded PhD Project (UK Students Only)
This project aims to develop computational and statistical methods to analyse fNIRS data and assess surgical expertise and neurocognitive performance. It combines neuroimaging, mathematical modelling, data science, and programming to support reliable quantitative surgical skill assessment.Automation of fNIRS Research by Ontological Analysis
Competition Funded PhD Project (UK Students Only)
This project aims to develop OntoNIRS into an operational ontology for reasoning about fNIRS experimental design and analysis. It combines computational neuroimaging, knowledge representation, logic, and natural language processing to support more systematic and potentially automated research workflows.Manifold Based Modelling of fNIRS Neuroimages
Competition Funded PhD Project (UK Students Only)
This project aims to develop a universal mathematical framework for addressing a broad range of fNIRS research questions. It will build on manifold-based models incorporating topology and group theory before validating the resulting framework on fNIRS data.Funding & Affiliations
University of Birmingham
EPSRC
BBSRC
NIH / NINDS
School of Computer Science