Computer Vision and Machine Learning (CVML)
The Computer Vision and Machine Learning (CVML) Research Group emerged as a result of cross-disciplinary interests in research and applications related to Computer Vision, Machine Learning and Medical Image Computing.
The main focus of the group is to research, develop and deploy novel methods for the analysis of visual information for medical and industrial applications. The group have led or been involved in a number of industry, EPSRC, FP7 and HEIF funded projects.
The ongoing emphasis is on developing new vision and machine learning algorithms and their transfer to real-world applications. The particular areas of interest include: Bayesian methodology for data modelling, pattern recognition and tracking; statistical shape analysis; deformation modelling for model-based recognition, segmentation and registration; medical imaging; intelligent energy management; data mining; and applications of deep learning.
The ongoing progress in the mathematical tools, the growing prevalence of very large datasets, ever-increasing computational power and progress in imaging devices established the computer vision and machine learning as mature scientific disciplines with a rapidly growing number of exploitations in wide spectrum of applications, such as machine condition monitoring, medical diagnosis, assistive living or autonomous vehicles to name just a few.
The CVML group have a wide ranging skills, combing expertise from different disciplines, including: engineering, physics, computing and media. The group activities are supported by a dedicated research laboratory with various vision systems including a number of static and dynamic 3D scanning devices, multi-camera acquisition and lighting systems, as well as dedicated GPU computing facilities.
The activities of the group are further supported by the international collaborations, including Information Processing and System Teams (ETIS) at Cergy-Pontoise University, I3S laboratory at the University of Cote d’Azur, or Signals and Images Laboratory at the Institute of the National Research Council of Italy (CNR) in Pisa, Computer Support for Medical Diagnosis & Therapy Procedures & Operations Group at the AGH University of Science and Technology in Kraków.
Reference Number: DTC25
A PhD (via MPhil) scholarship is available to work on “Advanced infrared imaging with machine learning surrogate models; maternal and neonatal care case study” project; application deadline: 06/01/2023.
For more information and to apply, please visit the jobs.ac.uk website
Reference Number: RS/21/23
A PhD (via MPhil) scholarship is available to work on “Efficient Deep Surrogate Models for Inverse Problems” project; application deadline: 26/01/2023.
For more information and to apply, please visit the Studentships page
- Medical Image Computations
- Computer Vision
- Machine Learning
- Motion analysis
- Data Analytics
- Data Mining
- Instrumentation and IoT
- Embedded systems
- Energy management
- “Wize-mirror” unobtrusive wellbeing monitoring system
- Software tools for medical image computations, including: detection, recognition segmentation and registration.
- LIVEfield – Software for video augmentation and automated shot composition
Ali, Sharib, Dmitrieva, Mariia, Ghatwary, Noha, Bano, Sophia, Polat, Gorkem, Temizel, Alptekin, Krenzer, Adrian, Hekalo, Amar, Guo, Yun Bo, Matuszewski, Bogdan J., Gridach, Mourad, Voiculescu, Irina, Yoganand, Vishnusai, Chavan, Arnav, Raj, Aryan, Nguyen, Nhan T., Tran, Dat Q., Huynh, Le Duy, Rittschera, Jens et al (2021) Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy. Medical Image Analysis, 70 (1). pp. 102002.
Guo, Yun Bo, Bernal, Jorge, Matuszewski, Bogdan J. (2020) Polyp Segmentation with Fully Convolutional Deep Neural Networks—Extended Evaluation Study. Journal of Imaging, 6 (7). pp. 69.
Guo, Li, Sim, Gavin, Matuszewski, Bogdan J. (2019) Inter-patient ECG classification with convolutional and recurrent neural networks. Biocybernetics and Biomedical Engineering, 39 (3). pp. 868-879.
Henriquez Castellano, Pedro, Matuszewski, Bogdan J., Andreu-Cabedo, Yasmina, Bastiani, Luca, Colantonio, Sara, Coppini, Giuseppe, D'Acunto, Mario, Favilla, Riccardo, Germanese, Danila et al (2017) Mirror mirror on the wall... an unobtrusive intelligent multisensory mirror for well-being status self-assessment and visualization. IEEE Transactions on Multimedia, 19 (7). pp. 1467-1481.
Bernal, Jorge, Tajbakhsh, Nima, Sanchez, F. Javier, Matuszewski, Bogdan J., Chen, Hao, Yu, Lequan, Angermann, Quentin, Romain, Olivier, Rustad, Bjorn et al (2017) Comparative Validation of Polyp Detection Methods in Video Colonoscopy: Results from the MICCAI 2015 Endoscopic Vision Challenge. IEEE Transactions on Medical Imaging, 36 (6). pp. 1231-1249.
Andreu, Yasmina, Chiarugi, Franco, Colantonio, Sara, Giannakakis, Giorgos, Giorgi, Daniela, Henriquez Castellano, Pedro, Kazantzaki, Eleni, Manousos, Dimitris, Marias, Kostas, Matuszewski, Bogdan, Pascali, Maria Antonietta, Pediaditis, Matthew, Raccichini, Giovanni, Tsiknakis, Manolis (2016) Wize Mirror - a smart, multisensory cardio-metabolic risk monitoring system/ Computer Vision and Image Understanding, 148 (1), pp. 3-22. July 2016. Wize Mirror - a smart, multisensory cardio-metabolic risk monitoring system Computer Vision and Image Understanding
Tao, Lili and Matuszewski, Bogdan J., (2016) Robust Deformable Shape Reconstruction from Monocular Video with Manifold Forest. Machine Vision and Applications, 27 (6). pp. 801-819.
Veta, Mitko, van Diest, Paul J., Willems, Stefan M., Wang, Haibo, Madabhushi, Anant, Cruz-Roa, Angel, Gonzalez, Fabio, Larsen, Anders B.L., Vestergaard, Jacob S. et al (2014) Assessment of algorithms for mitosis detection in breast cancer histopathology images. Medical Image Analysis, 20 (1). pp. 237-248.
Quan, Wei, Matuszewski, Bogdan J., and Shark, Lik (2015) Statistical shape modelling for expression-invariant face analysis and recognition. Pattern Analysis & Applications . pp. 1-17.
Quan, Wei, Matuszewski, Bogdan J., and Shark, Lik (2016) 3-D Face Recognition Using Geodesic-Map Representation and Statistical Shape Modelling. Lecture Notes in Computer Science, 9493 . pp. 199-212.
Song, Zhuoyi, Zhou, Yu and Juusola, Mikko (2017) Modeling elucidates how refractory period can provide profound nonlinear gain control to graded potential neurons. Physiological reports, 5
Song, ZH, Zhou, Yand Juusola, M (2016) Random Photon Absorption Model Elucidates How Early Gain Control in Fly Photoreceptors Arises from Quantal Sampling. Frontiers in Computational Neuroscience, 10 .
Pretorius, AJ, Zhou, Yu and Ruddle, R (2015) Visual parameter optimisation for biomedical image processing. BMC Bioinformatics, 16 (S9). pp. 1-13.
Furfaro, Roberto, Wibben, Daniel, R., Gaudet, Brian and Simo, Jules (2015) Terminal multiple surface sliding guidance for planetary landing: Development, tuning and optimization via reinforcement learning Journal of the Astronautical Sciences, Vol. 62(1), pp.73-99.
Simo, Jules, Furfaro, Roberto, and Mueting, Joel (2015) Performance evaluation of artificial neural network-based shaping algorithm for planetary pinpoint guidance In: Advances in the Astronautical Sciences. Advances in the Astronautical Sciences, 155. Univelt Inc, USA, pp. 2233-2248.
- 28 November – Dr Edward Sanderson presents a poster reporting on the AIdDeCo project at the STFC CDN+ ‘Cancer Theranostics Workshop’ in London.
- 18 September – AIdDeCo project team win the 1st first place for the “Depth prediction in simulated colonoscopy” task of the “SimCol-to-3D 2022 – 3D Reconstruction” sub-challenge hosted at the Medical Image Computing and Computer Assisted Intervention (MICCAI 2022) conference in Singapore.
- 29 July - CVML team paper (FCN-Transformer Feature Fusion for Polyp Segmentation, LNCS vol. 13413) was awarded 3rd place in the Best Paper category at the Medical Image Understanding and Analysis (MIUA) Conference.
- 27 - 29 July – Two papers from the CVML group are presented at this year Medical Image Understanding and Analysis (MIUA) Conference.
- July – FCBFormer polyp segmentation software has been made available on GitHub. The software provides state-of-the-art results as reported on the paper with code ranking website.
- 6 April – Professor Bogdan Matuszewski gives talk at the joint ELHT-UCLan MedTech Research Event.
- 17 – 18 February - Dr Edward Sanderson and Prof Bogdan Matuszewski give talks at the Complex Image Processing Workshop.
- 13 December - CVML team has been invited to submit a full application under the UKRI Develop basic Technologies in Sensing and Imaging call
- 8 November - Research Assistant has been appointed to work on the AIdDeCo project
- 13/14 October - CVML members participate in the DiRAC HPC-AI Advisory Council UK Conference
- 5 October - CVML members participate in the STFC Cancer Diagnosis Network+, virtual workshop focusing on ‘Applying Data Science Techniques to Cancer Diagnosis’
- 1 October - CVML team participate in the Medical Image Computing and Computer Assisted Intervention (MICCAI) 2021 Gastro-Intestinal Image ANAlysis (GIANA) Endoscopic Vision Challenge
- 30 September - CVML members participate in the DiRAC Nways Bootcamp training
- 12 July - Prof Bogdan Matuszewski chairs session on Biomarker Detection at the Medical Image Understanding and Analysis (MIUA) conference, Oxford, 12-14 July.
- 6 July - Prof Bogdan Matuszewski gives a talk at the STFC Cancer Diagnosis Network+ Showcase Workshop on ‘Machine Learning System for Decision Support and Computational Automation of Early Cancer Detection and Categorisation in Colonoscopy’
- 23 June - Mr Adnan A Sheikh, Robotic and Minimally Invasive Colorectal and General Surgery East Lancashire NHS Trusts, gives seminar on 'The physicist and the surgeon: the past, present and the future'
- 11 May - CVML group start collaboration with the THRIVE Research Centre (School of Community Health and Midwifery) on the proof of concept SKEL study funded by the LIFE Institute Research Starter Award
- 27 April - Prof Bogdan Matuszewski gives a talk at the Digital Health Workshop at the Academic Health Science Network for the North West Coast meeting
- 30 June - Application submission deadline for the 'Deep Learning Architectures for Bioimaging Multiscale Analysis; Form Cell to Full Body Scans' funded PhD project available at the CVML group. The project is to start from the 1st of October 2020. (application now closed)
- 18 May - Prof Bogdan Matuszewski has been awarded STFC CDN+ Proof of Concept funding for ‘Machine Learning System for Decision Support and Computational Automation of Early Cancer Detection and Categorisation in Colonoscopy’ collaborative project.
- 3 April - CVML team take part in the 2nd International Workshop and Challenge on Computer Vision in Endoscopy (EndoCV2020)
- 2 March - Dr Li Guo secures funding under Research 2 Market (R2M) programme.
- 17 December - Prof Bogdan Matuszewski delivers a at the Department of Signal Processing System, . The lecture has been co-organised by the of Society.lecture on Visual Information ProcessingWrocław University of Science and TechnologyPolish ChapterIEEE Signal Processing
- 6 December - Prof Bogdan Matuszewski to deliver a talk at the Durham University as part of the Institute of Physics North East Branch Public Lecture Series.
- 19 September - Prof Bogdan Matuszewski to deliver an invited keynote talk at the IEEE Signal Processing Symposium (SPSympo’2019).
- 19 September – Prof Bogdan Matuszewski to chair Image Processing Session at the Signal Processing Symposium (SPSympo 2019).
- 6 September - CVML is co-organising workshop on Visual Computing and Machine Learning for Biomedical Applications (ViMaBi’2019) at the 18th International Conference on Computer Analysis of Images and Patterns (CAIP).
- 24 July - Prof Frederic Precioso from University of Côte d'Azur, delivers talk on 'Deep Learning Techniques for Medical Applications'
- 22-23 - CVML is co-organising the 4th International Workshop on Image Processing Techniques and Applications (IPTA 2019).
- 4 July - Prof Bogdan Matuszewski is to deliver an invited talk at the National Astronomy Meeting (NAM2019) on 'Machine learning: What? How? When? – and should I care anyway?'
- May/July - Internship student from ENSEA works on 3D pose estimation project.
- 27 March - Prof Bogdan Matuszewski delivers an outreach talk on Visual Information Processing for Biomedical Applications at the Cardinal Newman College.
- 26 February - CVML contributes to the Special Session on GastroIntestinal Image Analysis- GIANA 2019.
- 27 November - CVML is holding a workshop on 'Challenges & Advances in Biomedical Image Computing' at the Joint Research Day organised by the University of Central Lancashire, the East Lancashire Clinical Commissioning Group and the East Lancashire Hospitals NHS Trust.
- September - UCLan team takes the second place at the Gastrointestinal Image ANAlysis (GIANA) SD Polyp Segmentation Challenge held at the Medical Image Computing and Computer Assisted Interventions (MICCAI) Conference (16-20 September 2018, Grenada, Spain)
- CVML is co-organising the 4th International Workshop on Image Processing Techniques and Applications (IPTA 2019) to be run in association with the 23rd conference on Medical Image Understanding and Analysis (MIUA 2019).
- August - A new MSc course in Applied Data Science has been approved to run from September 2019.
- July/September - A PhD student from the AGH University of Science and Technology works on cells motion analysis and image deformable registration as part of a summer internship at UCLan.
- July/August - An internship MSc student from the University Cote d’Azur (UCA) works on cells motion analysis and Generative Adversarial Networks (GANs) image synthesis.
- July/August - Two students, funded from the UCLan Undergraduate Research Internship Programme (UURIP), work on 3D object pose estimation from RGBD data and activity recognition from video.
- 25 April - Dr Bartłomiej Papież from the Big Data Institute at the University of Oxford, visits the CVML and delivers a talk on 'Complex Motion Modelling for Cancer Image Applications'.
- 18 April - Dr Lili Tao from University of the West of England / University of Bristol visits the CVML and delivers a talk on 'Computer Vision for Active and Assistive Living'.
- 11-12 April - Prof Bogdan Matuszewski visits the University Cote d’Azur (UCA) in Sophia Antipolis to deliver an invited talk on 'Visual Information Processing' at the H2020 DigiArt Project Consortium Workshop
- October - demonstration of the Autonomous broadCasting Editing System (ACES) at the International Conference on Computer Vision (ICCV) in Venice.
- September - Joint UCLan/UCA team wins the 'Surgical Workflow Analysis in SensorOR' Challenge held at the Medical Image Computing and Computer Assisted Interventions (MICCAI) Conference (10-14 September 2017, Quebec)
- September - UCLan team wins the Gastrointestinal Image ANAlysis (GIANA) Polyp Segmentation Challenge held at the Medical Image Computing and Computer Assisted Interventions (MICCAI) Conference (10-14 September 2017, Quebec)
- July/August - 2 MSc students form University Cote d’Azur (UCA) work on Surgical Workflow Analysis as part of a summer internship at UCLan
- 13 July - Prof Bogdan Matuszewski delivers an invited talk 'Application of Deep Learning Approaches for Machine Self-Monitoring' at the COMADEM 2017 Conference at UCLan.
- July - Best Student Presentation award at the 30th International Conference on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2017)
- 14-15 December - UCLan team to participate in the SEMEOTICONS project showcase in Pisa.
- July/August - 3 MSc students form Nice – Sophia Antipolis University work on the 'Circuit Reconstruction from Electron Microscopy Images' project as part of a summer internship at UCLan.
- 21-23 February - ECSON partners co-organise special session on Smart Embedded Biomedical Devices for In Situ Physiological Signal Processing – Smart – BIODEV 2016 at the 9th International Conference on Bio-Inspired Systems and Signal Processing BIOSIGNALS, Rome, Italy.
- 26-28 October - International Workshop on Big Data and Smart Sustainable Society at the 14th IEEE International Conference on Ubiquitous Computing and Communications (IUCC-2015), Liverpool, UK.
- 9 October - Joint UCLan/Nice team participates in the MICCAI’s 'EndoVis: Endoscopic Vision' Challenge.
- 5 October - UCLan team participates in the MICCAI’s 'GlaS: Gland Segmentation in Colon Histology Images' Challenge.
- January - The best paper award at the International Conference on Pattern Recognition Applications and Methods (ICRPAM) for the paper entitled: '3-D Shape Matching for Face Analysis and Recognition'
- Master of Science (MSc) in Applied Data Science
- Instrumentation and Control (EL2104)
- Computer Vision (EL3105)
- Undergraduate Final Year Projects (EL3995)
- Advanced Topics in Artificial Intelligence (ER4165)
- Artificial Intelligence and Machine Learning (EL4011)
- Internet of Things (EL4012)
- Programming with Data (EL4013)
- Visual Information Processing (EL4014)
- Digital Signal and Image Processing (EL4147)
- MSc Project (EL4895)
- Professor Bogdan Matuszewski
- Dr Edward Sanderson
- Dr Mara Bernabei
- Dr Aikaterini Fragaki
- Dr Shane O’Hehir
- Dr Jules Simo
- Dr Wei Quan
- Dr Zheng Xie
- Dr Yu Zhou
Internal transdisciplinary collaborations
- Professor Umesh Chauhan (Medicine)
- Professor Soo Downe (Midwifery Studies)
- Professor Charlie Frowd (Forensic Psychology)
- Dr Anastasia Topalidou (Biomedical Thermal Imaging)
- Professor Aymeric Histace (University of Cergy-Pontoise)
- Professor Frederic Precioso (Universite Cote d'Azur)
Former PhD students
- Dr Edward Sanderson
- Dr Essa Anas
- Dr Bartłomiej Papież
- Dr Li Yang Wang
- Dr Lili Tao
- Dr Yun Bo Guo
- Engineering and Computational Science for Oncology Network (ECSON)
- British Machine Vision Association
- The Medical Image Computing and Computer Assisted Intervention Society
- International Association of Pattern Recognition
- UK Industrial Vision Association
- The Institution of Engineering and Technology
- The Institute of Electrical and Electronics Engineers
- CV online
- A Synchronised Azure Kinect-based tracking system for the biomechanical Evaluation of Labour (SKEL)
- CT density heterogeneity as a marker of response to targeted agents in metastatic renal cancer
- Development of novel Thermal Imaging monitoring system for NEOnatal care (TI-Neo)
- Motion detection, categorisation and estimation with deep learning.
- Investigation of deep learning architectures for image segmentation applications
- Investigation and comparative analysis of random forest techniques for computer vision applications
- Simulation and prediction of energy consumption profiles for the built environment
- Registration of images with missing data
- 3D/4D imaging
- Gastrointestinal Image ANAlysis (GIANA)
- Surgical Workflow Analysis in the SensorOR
Externally funded projects:
- Machine Learning System for Decision Support and Computational Automation of Early Cancer Detection and Categorisation in Colonoscopy (AIdDeCo), STFC CDN+, 2020-2022
- LIVEfiled (Research in Broadcasting & Multimedia), Higher Education Innovation Funding (HEIF), 2016-2018.
- Self-resilient reconfigurable assembly system with in-process quality improvement, EPSRC Grant No. EP/K019368, 2013-2018, in collaboration with Warwick University (as the leading partner) and supported by BAE Systems, EnginSoft Ltd, Georgia College of Engineering, Georgia Institute of Technology, Hexagon Metrology Ltd, Jaguar and Land Rover, Stadco Ltd, Universities of Huddersfield, University of Michigan.
- SEMEiotic Oriented Technology for Individual’s CardiOmetabolic risk self-assessmeNt and Self-monitoring (SEMEOTICONS), EC 7th Framework, FP7-ICT-2013-10, Project No. 611516, in collaboration with: CNR (Italy), Foundation for Research and Technology – FORTH (Greece), Linköping University (Sweden), Norwegian University of Science and Technology Trondheim NTNU (Norway), CRNH (France), INTECS SPA (Italy), Hellenic Telecommunications & Telematics Applications Company - FORTHNET (Greece), DRACO Systems SL (Spain), COSMED SRL (Italy).
- Growing Autonomous System Mission Management (GAMMA), Department of Business Innovation and Skills, 2012-2015, in collaboration with North West Aerospace Alliance (NWAA), BAE Systems, National Nuclear Laboratory Ltd, University of Liverpool, Lancaster, Manchester and Salford.
- Dynamic Real-Time Three Dimensional Surface Sensor for Biomedical and Biometrics Applications, UCLan’s Research Equipment Development (RED) Fund, 2009-2010.
- Technology in Radiotherapy Feasibility Studies (TeRaFS), EPSRC grant under the Cross-Disciplinary Feasibility Account, Grant No. EP/H024913/1, 2009-2011, in collaboration with Christie Hospital; Liverpool John Moores University; including partners from: Rosemere Cancer Centre at the Royal Preston Hospital; ETIS CRNS Laboratory at ENSEA Cergy-Pontoise University (France); Otto von Guericke Universität Magdeburg (Germany).
- Dynamic Real-Time 3D Cameras for Computer Vision Applications, UCLan’s Teaching Equipment Fund, 2008.
- Engineering and Computational Science for Oncology Network (ECSON), EPSRC grant awarded under the Collaborating for Success through People call, Grant No. EP/F013698/1, 2007-2009, in collaboration with: Christie Hospital; Liverpool John Moores University; AGH University of Science and Technology (Poland); Jagiellonian University (Poland); Lyon Research Centre for Images and Intelligent Information Systems, CRNS (France), Signal and Image Processing Research Laboratory, CRNS (France), French National Institute for Research in Computer Science and Control, INRIA (France); Otto von Guericke Universität Magdeburg (Germany); Institute of Information Science and Technologies, CNR (Italy).
- Metrology Guided Radiation Therapy (MEGURATH), EPSRC Research Grant, Grant No. EP/D077540/1, 2007 - 2010, in collaboration with: Christie Hospital and Liverpool John Moores University.