Welcome to the Endo.AI webpage (1/5/2019-30/4/2020)

This project is funded by The Cancer Research UK under Innovation Award and is led by Oxford University Hospitals NHS Foundation Trust and has collaborators from Oxford University, University of Aberdeen and Middlesex University.

Project title:

Endo.AI – Real time automated endoscopic detection of oesophageal squamous cell cancer in early and precancerous stages

Summary:

The overarching aim of this project is to develop advanced Artificial Intelligence (AI) techniques that allow real-time endoscopic detection of squamous dysplasia and early oesophageal squamous cancer, which will be achieved through the application of state of the art segmentation and deep learning techniques based on high definition white light, narrow band imaging and multi-spectral endoscopy videos

Project partners:

Professor Barbara Braden (leader), Oxford University Hospitals NHS Foundation Trust, Oxford.

Dr. Stephen Taylor, MRC Weatherall Institute of Molecular Medicine, Oxford.

Dr. Wei Pang, Department of Computing Science, University of Aberdeen, Aberdeen.

Professor Xiaohong (Sharon) W. Gao, Department of Computer Science, Middlesex University, London.

Dr. Shahadate Rezvy, Project Researher, Department of Computer Science, Middlesex University, London.

Project Publications:

1. Sharib Ali, Mariia Dmitrieva, Noha Ghatwary, Sophia Bano, Gorkem Polat, Alptekin Temizel, Adrian Krenzer, Amar Hekalo, Yun Bo Guo, Bogdan Matuszewski, Mourad Gridach, Irina Voiculescu, Vishnusai Yoganand, Arnav Chavan, Aryan Raj, Nhan T. Nguyen, Dat Q. Tran, Le Duy Huynh, Nicolas Boutry, Shahadate Rezvy, Haijian Chen, Yoon Ho Choi, Anand Subramanian, Velmurugan Balasubramanian, Xiaohong W. Gao, Hongyu Hu, Yusheng Liao, Danail Stoyanov, Christian Daul, Stefano Realdon, Renato Cannizzaro, Dominique Lamarque, Terry Tran-Nguyen, Adam Bailey, Barbara Braden, James East, Jens Rittscher,, Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy, Medical Image Analysis, in press, 102002, 17 February, 2021.(IF=8.79)

2. Xiaohong (Sharon) Gao, Barbara Braden, Artefact Detection and Segmentation based on a Deep Learning system, Proceedings of the 2nd International Workshop and Challenge on Computer Vision in Endoscopy (EndoCV2020), Iowa, USA, 3rd April, 2020.

3. Shahadate Rezvy, Tahmina Zebin, Barbara Braden, Wei Pang, Stephen Taylor, Xiaohong W Gao, Transfer Learning For Endoscopy Disease Detection & Segmentation With Mask-RCNN Benchmark Architecture , Proceedings of the 2nd International Workshop and Challenge on Computer Vision in Endoscopy (EndoCV2020), Iowa, USA, 3rd April, 2020.

4. Sharib Ali,Felix Zhou Barbara Braden, Adam Bailey, Suhui Yang, Guanju Cheng, Pengyi Zhang, Xiaoqiong Li, Maxime Kayser, Roger D. Soberanis-Mukul, Shadi Albarqouni, Xiaokang Wang, Chunqing Wang, Seiryo Watanabe, Ilkay Oksuz, Qingtian Ning, Shufan Yang, Mohammad Azam Khan, Xiaohong W. Gao, Stefano Realdon, Maxim Loshchenov, Julia A Schnabel, James East, Georges Wagni`eres, Victor Loschenov, Enrico Grisan, Christian Dau, Walter Blonde, and Jens Rittscher, An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy , Nature Scientific Reports, 10, Article number: 2748 (2020).(IF=4.122)

5. Gao, XW, , Braden B, Zhang L, Taylor S, Pang W, Petridis M, Case-based Reasoning of a Deep Learning Network for Prediction of Early Stage of Oesophageal Cancer, , UKCBR 2019, in AI-2019, Cambridge, 2019.

6. Gao, Xiaohong W., , Barbara Braden, Steven Taylor, Wei Pang, Towards Real-Time Detection of Squamous Pre-Cancers from Oesophageal Endoscopic Videos, , IEEE 18th International Conference on Machine Learning and Application, (ICMLA 2019), December 16-19, 2019, Boca Raton, USA 2019.