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
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 (👋)
Applications are invited for the fully funded 1+3 years MRes+PhD or 4 years PhD MRC DTP studentship (including home tuition fees, annual stipend and consumables) starting in October 2025. Award details: Focus: Computer vision for surgical imaging applications Primary supervisor: Tom Vercauteren Secondary supervisor: Jonathan Shapey Third Supervisor: Dr Pavol Surda Funding type: 4-year fully-funded MRC DTP studentship including a stipend, tuition fees, research training and support grant (RTSG), and a travel and conference allowance.
The main MICCAI 2024 outcomes are now out and it’s a pleasure to announce that our research will be prominently featured. Congrats to the main authors from the group and all co-authors!
On 22nd of February we had our 5th “Science for Tomorrow’s Neurosurgery” group meeting. Live scribe of the conversations between patients and researchers. With exciting updates from both the NeuroPPEYE and NeuroHSI studies, the group were thrilled to learn of the progress we are making.
Tom Vercauteren has been appointed as Senior Editor for the highly-ranked Medical Image Analysis journal, an official journal of the MICCAI society. Sebastien Ourselin also features on the editorial board of the publication.
A prospective observational study to evaluate the use of an intraoperative hyperspectral imaging system in neurosurgery.
A prospective observational study to evaluate intraoperative hyperspectral imaging for real-time quantitative fluorescence-guided surgery of low-grade glioma.
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.
Through a comprehensive, integrated training programme, the Centre for Doctoral Training in Smart Medical Imaging
trains the next generation of medical imaging researchers.
The Functionally Accurate RObotic Surgery
(FAROS) H2020 project aims at improving functional accuracy through embedding physical intelligence in surgical robotics.
The GIFT-Surg
project is an international research effort developing the technology, tools and training necessary to make fetal surgery a viable possibility.
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.
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.
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.
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.
The Wellcome / EPSRC Centre for Medical Engineering
combines fundamental research in engineering, physics, mathematics, computing, and chemistry with medicine and biomedical research.
Pathways to clinical impact
Moon Surgical
has partnered with us to develop machine learning for computer-assisted surgery. More information on our press release.
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
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.
Tom Vercauteren worked for 10 years with Mauna Kea Technologies
(MKT) before resuming his academic career.
Medtronic
is the industrial sponsor of Tom Vercauteren’s Medtronic / Royal Academy of Engineering Research Chair in Machine Learning for Computer-Assisted Neurosurgery.
Exemplar outputs of our research
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.
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 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.
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.
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.
We contribute to MONAI, a PyTorch-based, open-source framework for deep learning in healthcare imaging, part of PyTorch Ecosystem.
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 is a freely available, community-supported open-source toolkit for research and education in medical image registration using deep learning (📖).
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 (📖).”
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 (📖).”
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 is an open-source C++ and Python API for acquiring, processing and encoding video streams in real time (📖).
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.
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