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

**CAI4CAI**

About us

King's College London logo

We are based at King’s College London
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Surgical assistance

Our engineering research aims at improving surgical & interventional sciences

Multidisciplinarity

We take a multidisciplinary, collaborative approach to solve clinical challenges (đź“–)

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London

Our labs are located in St Thomas’ hospital, a prominent London landmark

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Machine learning

We design learning-based approaches for multi-modal reasoning

Medical imaging

Medical imaging is a core source of information in our research

Computational biophotonics

We design intelligent systems exploiting information captured by safe light

Contextual AI

We thrive at providing the right information at the right time to the surgical team and embrace human/AI interactions (đź“–)

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Translational research

Strong industrial links are key to accelerate translation of cutting-edge research into clinical impact

Open culture

We support open source, open access and involve patients in our research

Recent posts

Collaborative research

NeuroHSI

NeuroHSI

A prospective observational study to evaluate the use of an intraoperative hyperspectral imaging system in neurosurgery.

NeuroPPEye

NeuroPPEye

A prospective observational study to evaluate intraoperative hyperspectral imaging for real-time quantitative fluorescence-guided surgery of low-grade glioma.

CDT SIE

CDT SIE

The Centre for Doctoral Training in Surgical & Interventional Engineering (CDT SIE) is an innovative three-and-a-half year PhD training program aiming to deliver translational research and transform patient pathways.

CDT SMI

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

FAROS

The Functionally Accurate RObotic Surgery (FAROS) H2020 project aims at improving functional accuracy through embedding physical intelligence in surgical robotics.

GIFT-Surg

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

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

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

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

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

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

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Moon Surgical

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

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 SĂ©bastien 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.

ico**metrix**

icometrix

icometrix is the consortium lead of the icovid project.

Intel (previously COSMONiO)

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

Mauna Kea Technologies

Tom Vercauteren worked for 10 years with Mauna Kea Technologies (MKT) before resuming his academic career.

Medtronic

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

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Intrapapillary Capillary Loop (IPCL) Classification

Intrapapillary Capillary Loop (IPCL) Classification

We provide open source code and open access data for our paper “GarcĂ­a-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 (đź“–).”

NiftyNet: Open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy

NiftyNet: Open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy

[unmaintained] NiftyNet is a TensorFlow 1.x based open-source convolutional neural networks (CNN) platform for research in medical image analysis and image-guided therapy (đź“–). It has been superseeded by MONAI.

Python Unified Multi-tasking API (PUMA)

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: Simple frame grabbing API

GIFT-Grab is an open-source C++ and Python API for acquiring, processing and encoding video streams in real time (đź“–).

The CAI4CAI team

Principal investigators

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Tom Vercauteren

CAI4CAI lead

Professor of Interventional Image Computing

King's College London, United Kingdom

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SĂ©bastien Ourselin

Professor of Healthcare Engineering

King's College London, United Kingdom

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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

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Aaron Kujawa

Research Associate

King's College London, United Kingdom

Groups: Tom, Jonathan

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Anisha Bahl

PhD Student

King's College London, United Kingdom

Groups: Tom, Mads

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Bappaditya (Rick) Debnath

Research Associate

King's College London, United Kingdom

Groups: Tom, Jonathan

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Charlie Budd

Research Software Engineer

King's College London, United Kingdom

Group: Tom

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Christopher E. Mower

Research Associate

King's College London, United Kingdom

Groups: Christos, Tom

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Luis Carlos Garcia Peraza Herrera

Research Associate in Computer Vision and Machine Learning

King's College London, United Kingdom

Group: Tom

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Marina Ivory

Research Associate

King's College London, United Kingdom

Groups: Jonathan, Tom

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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

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Maxence Boels

PhD Student

King's College London, United Kingdom

Groups: Seb, Prokar

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Meng Wei

PhD Student

King's College London, United Kingdom

CDT Smart Medical Imaging

Groups: Tom, Miaojing, Prokar

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Muhammad Asad

Research Fellow

King's College London, United Kingdom

Group: Tom

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Navodini Wijethilake

PhD Student

King's College London, United Kingdom

Groups: Jonathan, Tom

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Oluwatosin Alabi

PhD Student

King's College London, United Kingdom

EPSRC CDT in Smart Medical Imaging

Groups: Miaojing, Tom

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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

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Peichao Li

PhD Student

King's College London, United Kingdom

Groups: Tom, Jonathan

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Silvère Ségaud

Research Associate

King's College London, United Kingdom

Groups: Tom, Jonathan, Yijing

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Tangqi Shi

PhD Student

King's College London, United Kingdom

Group: Tom Booth, Tom

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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

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Yijing Xie

L’Oréal UK&I and UNESCO for Women in Science Rising Talent Fellow

King's College London, United Kingdom

Group: Tom

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Zhe Han

Visiting PhD Student

King's College London, United Kingdom

Beijing Institute of Technology, China

Group: Tom

Affiliated research team members

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Helena Williams

PhD Student

KU Leuven, Belgium

King's College London, United Kingdom

Groups: Jan, Jan, Tom

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Martin Huber

PhD Student

King's College London, United Kingdom

Groups: Christos, Tom

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Mengjie Shi

PhD Student

King's College London, United Kingdom

Groups: Wenfeng, Tom

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Michael Ebner

CEO and co-founder, Hypervision Surgical

Hypervision Surgical Ltd, United Kingdom

King's College London, United Kingdom

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Samuel Joutard

PhD Student

King's College London, United Kingdom

Groups: Marc, Tom

Alumni

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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.

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