Computer Assisted Navigation, Diagnosis and Intervention (CANDI)

CANDI

Computer Assisted Navigation, Diagnosis and Intervention (CANDI) is a research group applying artificial intelligence, computational modelling and software engineering on surgical procedures and medical interventions. We aim to translate our methodologies and innovations to improve surgical navigation, disease diagnosis and minimally invasive interventions.

We are members of UCL Centre for Medical Image Computing (CMIC) and Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS). Our research spans across multidisciplinary applications including those for prostate cancer, pancreatic cancer, fetal medicine, interventional radiology.

We are always looking for bright minds to join our team as postgraduate students or postdoctoral research fellows. Full scholarships are available through the EPSRC Centre for Doctoral Training in Intelligent, Integrated Imaging In Healthcare (i4health), among other opportunities. Please get in touch for further information.

Members 

Research Staff and Students

• Dean Barratt (Co-Lead, Professor)
• Zachary Baum (PhD Student)
• Ester Bonmati (WEISS Senior Research Fellow)
• Yunguan Fu (Research Assistant)
• Iani Gayo (PhD Student)
• Yipeng Hu (Co-Lead)
• Qi Li (PhD Student)
• Yiwen Li (PhD Student)
• Nina Montana Brown (PhD Student)
• Zhe Min (Postdoctoral Research Fellow)
• Mark Pinnock (PhD Student)
• Rachael Rodell (Research Assistant)
• Shaheer Saeed (PhD Student)
• Ziyi Shen (Postdoctoral Research Fellow)
• Qianye Yang (PhD Student)
• Wen Yan (Research Assistant, Visiting PhD Student)

Students undertaking research projects

Alumni

• Ruoxi Gao
• Remi Delaunay
• Alex Grimwood 
• Zbigniew Wojna
• Nooshin Ghavami 
• Eli Gibson 
• Paul Martin 
• Barbara Villarini 

We as a group have diverse expertise in lecturing, tutoring, project supervision and organising advanced computing-lab workshops, contributing to a variety of UCL modules including Machine Learning in Medical Imaging, Artificial Inteligence in Surgery and Intervention, Introduction to Deep Learning, Computing in Medicine, Information Processing in Medical Imaging, Image Assisted Surgery and Therapy and Programming Foundation for Medical Image Analysis. The main topics include programming, scientific computing, machine learning, statistical modelling and software development. Prof Dean Barratt is the Director of Studies in the UCL Department of Medical Physics and Biomedical Engineering. As our advancing translational research, we are also experienced in clinician training for innovative medical device and introductory training in medical device regulations.