CAI4CAI
We are an academic research group focusing on Contextual Artificial Intelligence for Computer Assisted Interventions.
CAI4CAI is embedded in the School of Biomedical Engineering & Imaging Sciences at King’s College London, UK
About us
We are based at King’s College London
Our engineering research aims at improving surgical & interventional sciences
We take a multidisciplinary, collaborative approach to solve clinical challenges (📖)
Our labs are located in St Thomas’ hospital, a prominent London landmark
We design learning-based approaches for multi-modal reasoning
Medical imaging is a core source of information in our research
We design intelligent systems exploiting information captured by safe light
We thrive at providing the right information at the right time to the surgical team and embrace human/AI interactions (📖)
Strong industrial links are key to accelerate translation of cutting-edge research into clinical impact
We support open source, open access and involve patients in our research (👋)
Recent posts
![PhD opportunity [October 2025 start] on "Computational stereovision synthesis from monocular neuroendoscopy"](/post/2024-09-24-monostereo-phd/featured_hued20e1bf7ce74a637cb156edc841b2e2_596404_5448495fef26cbb2e5071cb1ab8510f1.webp)
Collaborative research
NeuroHSI
A prospective observational study to evaluate the use of an intraoperative hyperspectral imaging system in neurosurgery.
NeuroPPEye
A prospective observational study to evaluate intraoperative hyperspectral imaging for real-time quantitative fluorescence-guided surgery of low-grade glioma.
CDT AE-PSI
The EPSRC Centre for Doctoral Training in Advanced Engineering in Personalised Surgery & Intervention (CDT AE-PSI) is an innovative three-and-a-half year PhD training program aiming to deliver translational research and transform patient pathways.
CDT SMI
Through a comprehensive, integrated training programme, the Centre for Doctoral Training in Smart Medical Imaging trains the next generation of medical imaging researchers.
FAROS
The Functionally Accurate RObotic Surgery (FAROS) H2020 project aims at improving functional accuracy through embedding physical intelligence in surgical robotics.
GIFT-Surg
The GIFT-Surg project is an international research effort developing the technology, tools and training necessary to make fetal surgery a viable possibility.
icovid
The icovid project focuses on AI-based lung CT analysis providing accurate quantification of disease and prognostic information in patients with suspected COVID-19 disease.
K-CSC
Up to 100 King’s-China Scholarship Council PhD Scholarship programme (K-CSC) joint scholarship awards are available per year to support students from China who are seeking to start an MPhil/PhD degree at King’s College London.
MRC DTP BiomedSci
The integrated and multi-disciplinary approach of the MRC Doctoral Training Partnership in Biomedical Sciences (MRC DTP BiomedSci) to medical research offers a wealth of cutting-edge PhD training training opportunities in fundamental discovery science, translational research and experimental medicine.
TRABIT
The Translational Brain Imaging Training Network (TRABIT) is an interdisciplinary and intersectoral joint PhD training effort of computational scientists, clinicians, and the industry in the field of neuroimaging.
Wellcome / EPSRC CME
The Wellcome / EPSRC Centre for Medical Engineering combines fundamental research in engineering, physics, mathematics, computing, and chemistry with medicine and biomedical research.
Spin-outs and industry collaborations
Pathways to clinical impact
Moon Surgical
Moon Surgical has partnered with us to develop machine learning for computer-assisted surgery. More information on our press release.
Hypervision Surgical Ltd
Following successful in-patient clinical studies of CAI4CAI’s translational research on computational hyperspectral imaging system for intraoperative surgical guidance, Hypervision Surgical Ltd was founded by Michael Ebner, Tom Vercauteren, Jonathan Shapey, and Sébastien Ourselin.
In collaboration with CAI4CAI, Hypervision Surgical’s goal is to convert the AI-powered imaging prototype system into a commercial medical device to equip clinicians with advanced computer-assisted tissue analysis for improved surgical precision and patient safety.
Intel (previously COSMONiO)
Intel is the industrial sponsor of Theo Barfoot’s’s PhD on Active and continual learning strategies for deep learning assisted interactive segmentation of new databases.
Mauna Kea Technologies
Tom Vercauteren worked for 10 years with Mauna Kea Technologies (MKT) before resuming his academic career.
Medtronic
Medtronic is the industrial sponsor of Tom Vercauteren’s Medtronic / Royal Academy of Engineering Research Chair in Machine Learning for Computer-Assisted Neurosurgery.
Open research
Exemplar outputs of our research
CAI4CAI on github
We support open source and typically use github to disseminate our research. Repositories can be found on our group organisation (CAI4CAI) or individual member github profiles.
Transferring Relative Monocular Depth to Surgical Vision with Temporal Consistency
This work makes significant strides in the field of monoocular endoscopic depth perception, drastically improving on previous methods. The task of monocular depth perception demonstrates a nuanced understanding of the surgical scene, and could act as a vital building block in future technologies. To acheive our results, we leverage large vision transformers trained on huge natural image datasets and fine tuned to our ensembled meta dataset of sugical videos. Read more about it in our pre-print, or get our model here.
FastGeodis: Fast generalised geodesic distance transform
FastGeodis is an open-source package that provides efficient implementations for computing Geodesic and Euclidean distance transforms (or a mixture of both), targetting efficient utilisation of CPU and GPU hardware.
A spatio-temporal atlas of the developing fetal brain with spina bifida aperta
We make publicly available a spatio-temporal fetal brain MRI atlas for SBA. This atlas can support future research on automatic segmentation methods for brain 3D MRI of fetuses with SBA.
Image Compositing for Segmentation of Surgical Tools without Manual Annotations
We have recently published the paper “Garcia-Peraza-Herrera, L. C., Fidon, L., DEttorre, C. Stoyanov, D., Vercauteren, T., Ourselin, S. (2021). Image Compositing for Segmentation of Surgical Tools without Manual Annotations. Transactions in Medical Imaging (📖)”. Inspired by special effects, we introduce a novel deep-learning method to segment surgical instruments in endoscopic images.
MONAI (Medical Open Network for AI): PyTorch for medical imaging
We contribute to MONAI, a PyTorch-based, open-source framework for deep learning in healthcare imaging, part of PyTorch Ecosystem.
Learning joint Segmentation of Tissues And Brain Lesions (jSTABL) from task-specific hetero-modal domain-shifted datasets
Open source PyTorch implementation of “Dorent, R., Booth, T., Li, W., Sudre, C. H., Kafiabadi, S., Cardoso, J., … & Vercauteren, T. (2020). Learning joint segmentation of tissues and brain lesions from task-specific hetero-modal domain-shifted datasets. Medical Image Analysis, 67, 101862 (📖).”
DeepReg: Medical image registration using deep learning
DeepReg is a freely available, community-supported open-source toolkit for research and education in medical image registration using deep learning (📖).
Intrapapillary Capillary Loop (IPCL) Classification
We provide open source code and open access data for our paper “García-Peraza-Herrera, L. C., Everson, M., Lovat, L., Wang, H. P., Wang, W. L., Haidry, R., … & Vercauteren, T. (2020). Intrapapillary capillary loop classification in magnification endoscopy: Open dataset and baseline methodology. International journal of computer assisted radiology and surgery, 1-9 (📖).”
Fetal brain MRI reconstruction (NiftyMIC)
NiftyMIC is a Python-based open-source toolkit for research developed within the GIFT-Surg project to reconstruct an isotropic, high-resolution volume from multiple, possibly motion-corrupted, stacks of low-resolution 2D slices. Read “Ebner, M., Wang, G., Li, W., Aertsen, M., Patel, P. A., Aughwane, R., … & David, A. L. (2020). An automated framework for localization, segmentation and super-resolution reconstruction of fetal brain MRI. NeuroImage, 206, 116324 (📖).”
Python Unified Multi-tasking API (PUMA)
PUMA provides a simultaneous multi-tasking framework that takes care of managing the complexities of executing and controlling multiple threads and/or processes.
GIFT-Grab: Simple frame grabbing API
GIFT-Grab is an open-source C++ and Python API for acquiring, processing and encoding video streams in real time (📖).
The CAI4CAI team
Principal investigators
Tom Vercauteren
CAI4CAI lead
Professor of Interventional Image Computing
King's College London, United Kingdom
Jonathan Shapey
Clinical Academic and Consultant Neurosurgeon
King's College London, United Kingdom
King's College Hospital NHS Foundation Trust, United Kingdom
Research team members
Lorena Garcia-Foncillas Macias
MRes/PhD Student
King's College London, United Kingdom
Groups: Jonathan, Tom
Matthew Elliot
Neurosurgical Clinical Research Fellow and PhD Student
King's College London, United Kingdom
King's College Hospital NHS Foundation Trust, United Kingdom
Groups: Jonathan, Tom
Meng Wei
PhD Student
King's College London, United Kingdom
CDT Smart Medical Imaging
Groups: Tom, Miaojing
Oluwatosin Alabi
PhD Student
King's College London, United Kingdom
EPSRC CDT in Smart Medical Imaging
Groups: Miaojing, Tom
Oscar MacCormac
Neurosurgery Clinical Research Fellow and PhD Student
King's College London, United Kingdom
King's College Hospital NHS Foundation Trust, United Kingdom
Groups: Jonathan, Tom
Silvère Ségaud
Research Associate
King's College London, United Kingdom
Groups: Tom, Jonathan, Yijing
Theo Barfoot
PhD Student
King's College London, United Kingdom
Imperial College London, United Kingdom
EPSRC CDT in Smart Medical Imaging
Groups: Tom, Ben, Jonathan
Yijing Xie
L’Oréal UK&I and UNESCO for Women in Science Rising Talent Fellow
King's College London, United Kingdom
Affiliated research team members
Helena Williams
Postdoctoral fellow
KU Leuven, Belgium
King's College London, United Kingdom
Groups: Jan, Jan, Tom
Michael Ebner
CEO and co-founder, Hypervision Surgical
Hypervision Surgical Ltd, United Kingdom
King's College London, United Kingdom
Alumni
CAI4CAI alumni
See our previous lab members
Open positions
You can browse our list of open positions (if any) here, as well as get an insight on the type of positions we typically advertise by browsing through our list of previous openings. We are also supportive of hosting strong PhD candidates and researchers supported by a personal fellowship/grant.
Please note that applications for the listed open positions need to be made through the University portal to be formally taken into acount.
.js-id-open-position![PhD opportunity [October 2025 start] on "Computational stereovision synthesis from monocular neuroendoscopy"](/post/2024-09-24-monostereo-phd/featured_hued20e1bf7ce74a637cb156edc841b2e2_596404_4e86c29e72dd12687398cee06fcf7648.webp)
![PhD opportunity [October 2024 start] on "Text promptable semantic segmentation of volumetric neuroimaging data"](/post/2023-10-04-textpromptseg-phd/featured_hu9cffe8f92aac5dca23024ca6f87c917b_371547_7df2dde8ca4446a42643f0f6c9aa5173.webp)
![[Job] Research Coordinator - King's College Hospital NHS Foundation Trust](/post/2022-12-01-researchcoordinator/featured_hua76f5912eb9b14abdd3b03b1888d5939_43123_a1cd9aeadbd197bd99680d2e60431021.webp)
![PhD opportunity [February 2024 start] on "Incorporating Expert-consistent Spatial Structure Relationships in Learning-based Brain Parcellation"](/post/2022-11-15-twaiparcellation/featured_huf3572e07bd271a265b9d8fea5a6f8a22_671053_f60b5702436a7c73c9436b5617461a3d.webp)
![PhD opportunity [February 2024 start] on "Accurate automated quantification of spine evolution — it’s about time!"](/post/2022-11-13-spinequantification/featured_hue441289d11fb9b36a14fd6682530aba5_56766_843334c57cbe7ac89a60195f491545fb.webp)
![PhD opportunity [February 2024 start] on "Physically-informed learning-based beamforming for multi-transducer ultrasound imaging"](/post/2021-11-03-usbeamforming/featured_hu0c2ac008fe8d40090cad5bcb6e5c49c2_122139_68a08eaf46acc68671dda8a077011116.webp)
![PhD opportunity [June 2022 start] on "Computational approaches for quantitative fluorescence-guided neurosurgery"](/post/2022-03-24-qfhsiphd/featured_hubda89bb1d49c7c323a29882835d0878a_127129_7d53961b683f7dc1ed5344a31ac924a5.webp)
![[CfP] MedIA Special Issue on Explainable and Generalizable Deep Learning Methods for Medical Image Computing](/post/2021-05-24-media-si/featured_hu18711ec9c301c0d9f7b94fa95b196c10_174992_f9f301456786a6c535f1ba0feca4f9bb.webp)
Contact
- 1 Lambeth Palace Road, London, SE1 7EU, UK
- Becket House 9th floor
- Find us on GitHub
- Find us on Vimeo