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Medical Physics Laboratory

ΔΕΙΤΕ ΣΤΗΝ ΕΝΟΤΗΤΑ: Demos |Datasets |


Associate Professor, Medical School, National and Kapodistrian University of Athens


    Mikras Asias 75 (GOUDI), 11527, Athens, Greece
    Tel: +30210 7462437 -  Email: cloukas[at]med.uoa[dot]gr

    • Ph.D. in Medical Physics, Department of Medical Physics & Bioengineering, University College London, UK, 2002
    • M.Sc. in Medical Physics, Department of Physics, University of Surrey, UK, 1998
    • B.Sc. (Hons) in Physics, Department of Physics, University of Athens, 1996
    • Associate Professor, Medical Physics Laboratory, University of Athens, 2022-present
    • Assistant Professor, Medical Physics Laboratory-Simulation Center, University of Athens, 2013-2022
    • Lecturer, Medical Physics Laboratory-Simulation Center, University of Athens, 2010-2013
    • Project Manager (Medical Informatics), Datamed, ATKO-Soft, Athens, 2007-2009
    • Senior Research Scientist, FORTH-Photonics (Diagnostic Imaging Technologies), Athens, 2005-2006
    • Postdoctoral Scientist, GlaxoSmithKline (GSK), Addenbrookes Centre for Clinical Investigation, Cambridge, UK. Sobell Department of Motor Neuroscience & Movement Disorders, Institute of Neurology, UCL, UK, 2002-2004
    • Doctoral (PhD) Researcher, Gray Cancer Institute, Mount Vernon Hospital, Northwood, UK, 1998-2001
    • Medical Physics
    • Medical Informatics
    • Lectures in MSc courses (e.g. Medical Radiation Physics, Biomedical Technology, Minimally Invasive and Robotic Surgery, Cardiology Nursing-Intensive Care Units, etc.)
    • Instructor in medical simulation training programs (e.g. VR-based surgical skills, more info here)
    • Member of: IEEE, INSTICC, IPEM, Hellenic MPA, Technologies and Simulation Committee (Consortium of American College of Surgeons-Accredited Education Institutes)
    • Editorial Board/Topic Editor: IJMRCAS, IJARA, Applied Sciences
    • Reviewer for Journals (Med Im Anal, ΙΕΕE Τ-ΒΜΕ, IEEE T-HMS, IEEE J-BHI, IJCARS, IJMRCAS, CMPB, CBM, MBEC, PMB, etc.)
    • Reviewer for R&D grant proposals (e.g. GSRT, NSRF, University research funds, Overseas funding organizations)

    My research interests lie primarily in the area of Artificial Intelligence in Surgery (specifically  Surgical Data Science), using computer vision, signal analysis and machine learning techniques. In the past I was affiliated with the following research centers: GSK R&DInstitute of NeurologyMedical Imaging Group – UCL, and Gray Cancer Institute.

    Currently my research work focuses on:

    • Video processing of surgical procedures
    • Context aware assistance in surgical education and practice
    • Skills assessment in surgery
    • Virtual and augmented reality systems for surgical training

    In my previous posts I was involved with (and I am still interested in):

    • Histopathological image analysis
    • Brain signal analysis
    • Spectral Imaging
    • PACS and telemedicine systems

    See below for a list of my publications. Here are some demos and datasets from my research work.


    Journals (with impact factor)

    • O.P. Chatzipanagiotou, C. Loukas, et al., 'Artificial intelligence in hepatocellular carcinoma diagnosis: a comprehensive review of current literature', J Gastroent Hepatol, 2024. Paper

    • C. Loukas, et al., 'Prediction of remaining surgery duration in laparoscopic videos based on visual saliency and the transformer network', Int. J. Med. Robot. Comput. Assist. Surg. 20(2), e2632, 2024. Paper

    • D. Koumatzidis, I. Seimenis, C. Loukas, T. Constantinidis and A. Adamopoulos, ‘Impact of quarantine and vaccination policies on viral load’, Applied Sciences, 13(1), 396 (special issue: New Trends in Biosciences III), 2023. Paper

    • G. Kourelis, M. Kanakis, C. Loukas, et al., 'Efficiency and safety of patent ductus arteriosus surgical ligation in extremely low birth weight infants without chest tube placement', J Pediatr Intensive Care, 12(04): 264-270, 2023 . Abstract

    • A. Gazis, P. Karaiskos and C. Loukas, ‘Surgical gesture recognition in laparoscopic tasks based on the Transformer network and self-supervised learning’, Bioengineering, 9(12), 737 (special issue: Artificial Intelligence in Surgery), 2022. Paper

    • R. Sharma, P. Tsiamyrtzis, A.G. Webb, I. Seimenis, C. Loukas, E. Leiss, and N.V. Tsekos, ‘A deep learning approach to upscaling “low-quality” MR images: an in silico comparison study based on the UNet framework’, Applied Sciences, 12(22), 11758, 2022. Paper

    • C. Loukas, et al., ‘Multiple instance convolutional neural network for gallbladder assessment from laparoscopic images’, Int J Med Robot Comput Assist Surg, 18(6):e2445, 2022. Abstract

    • C. Loukas and N. Kelekis, ‘Editorial for "MRI-Based Multiple Instance Convolutional Neural Network (MICNN) for Increased Accuracy in the Differentiation of Borderline and Malignant Epithelial Ovarian Tumors"’, J Magn Reson Imaging, 56(1):182-183, 2022. Abstract

    • P. Marentakis, P. Karaiskos, V. Kouloulias, N. Kelekis, S. Argentos, N. Oikonomopoulos and C. Loukas, ‘Lung cancer histology classification from CT images based on radiomics and deep learning models’, Med Biol Eng Comput, 59(1), 215-226, 2021. Abstract

    • C. Loukas, et al., ‘Patch-based classification of gallbladder wall vascularity from laparoscopic images using deep learning’, Int J Comput Assist Rad Surg, 16(1), 103-113, 2021. Abstract

    • C. Loukas, et al., ‘Surgical performance analysis and classification based on video annotation of laparoscopic tasks’, JSLS-Journal of the Society of Laparoendoscopic Surgeons, 24(4):e2020.00057 (1-10), 2020. Paper

    • C. Loukas and N.P. Sgouros, ‘Multi-instance multi-label learning for surgical image annotation’, Int J Med Robot Comput Assist Surg, 16(2):e2058 (1-12), 2020. Abstract

    • E. Dokoutsidou, M. Alodat, C. Mavrogiannis, K. Georgiou, E. Giannakopoulou, P. Galanis, C. Loukas, et al., ‘Performance assessment of subjects with nursing education trained in sigmoidoscopy by means of a simulator’, Gastroenterol Nurs, 43(6), 411-421, 2020. Abstract

    • M. Varras, C. Loukas, et al., ‘Comparison of laparoscopic surgical skills acquired on a virtual reality simulator and a box trainer: an analysis for obstetrics-gynecology residents’, Clin Exp Obstet Gynecol, 47(5), 755-763, 2020. Paper

    • M.N. Varras, N. Nikiteas, V.K. Varra, F.N. Varra, E. Georgiou and C. Loukas, ‘Role of laparoscopic simulators in the development and assessment of laparoscopic surgical skills in laparoscopic surgery and gynecology’, World Acad Sci J, 2(2), 65-76, 2020. Paper

    • C. Loukaset al., ‘Keyframe extraction from laparoscopic videos based on visual saliency detection’, Comp Meth Prog Biomed, 165, 13-23, 2018. Abstract

    • C. Loukas, ‘Video content analysis of surgical procedures’, Surg Endosc, 32(2):553-568, 2018. Abstract

    • N.P. Sgouros, C. Loukaset al., ‘An automated skills assessment framework for laparoscopic training tasks’, Int J Med Robot Comput Assist Surg, 14(1):e1853 (1-10), 2018. Abstract

    • N. Oussi, C. Loukaset al., ‘Video analysis in basic skills training: a way to expand the value and use of BlackBox training’, Surg Endosc, 32(1):87-95, 2018. Abstract

    • V. Lahanas, C. Loukaset al., ‘Virtual reality-based assessment of basic laparoscopic skills using the Leap Motion controller’, Surg Endosc, 31(12):5012-5023, 2017. Abstract

    • C. Loukaset al., ‘Shot boundary detection in endoscopic surgery videos using a variational Bayesian framework’, Int J Comput Assist Rad Surg, 11(11):1937-1949, 2016. Abstract

    • C. Loukaset al., ‘Simulation-based medical training and assessment in the Medical Physics Lab-Simulation Center (MPLSC)’, J Surg Ed, 73(6):1081-1084, 2016. Abstract

    • C. Loukas and E. Georgiou, ‘Performance comparison of various feature detector-descriptors and temporal models for video-based assessment of laparoscopic skills’, Int J Med Robot Comput Assist Surg, 12(3):387-98, 2016. Abstract

    • V. Lahanas, C. Loukas and E. Georgiou, ‘A simple sensor calibration technique for estimating the 3D pose of endoscopic instruments’, Surg Endosc, 30(3):1198-204, 2016. Abstract

    • V. Lahanas, E. Georgiou and C. Loukas, ‘Surgical simulation training systems: box trainers, virtual reality and augmented reality simulators’, Int J of Adv Rob Autom, 1(2):1-9, 2016. Abstract

    • V. Peppa, E. Pantelis, E. Pappas, V. Lahanas, C. Loukas and P. Papagiannis, ‘A user-oriented procedure for the commissioning and quality assurance testing of treatment planning system dosimetry in high-dose-rate brachytherapy’, Brachytherapy, 15(2):252-62, 2016. Abstract

    • E. Drakou, M.A. Kanakis, L. Papadimitriou, N. Iacovidou, N. Vrachnis, S. Nicolouzos, C. Loukas and A. Lioulias, ‘Changes in simple spirometric parameters after lobectomy for bronchial carcinoma’, J Cardiovasc Thorac Res, 7(2):68-71, 2015. Abstract

    • M.A. Kanakis, C. Loukaset al., ‘eComment. How trainees perform and develop their skills on the simulator’, Interact Cardiovasc Thorac Surg, 20(1):5-6, 2015. Abstract

    • V. Lahanas, C. Loukaset al., ‘A novel augmented reality simulator for skills assessment in minimal invasive surgery’, Surg Endosc, 29(8):2224-34, 2015. Abstract

    • C. Loukas and E. Georgiou, ‘Smoke detection in endoscopic surgery videos: A first step towards retrieval of semantic events’,  Int J Med Robot Comput Assist Surg, 11(1), 80-94, 2015. Abstract

    • C. Loukaset al., ‘The effect of mixed-task basic training in the acquisition of advanced laparoscopic skills’, Surg Innov, 22(4):418-25, 2015. Abstract

    • C. Loukaset al., ‘Breast cancer characterization based on image classification of tissue sections visualized under low magnification’, Comput Math Methods Med, v.2013, ID: 829461, 2013. Abstract

    • C. Loukaset al., ‘The role of hand motion connectivity in the performance of laparoscopic procedures on a virtual reality simulator’, Med Biol Eng Comput, 51(8), 911-922, 2013. Abstract

    • C. Loukaset al., ‘An integrated approach to endoscopic instrument tracking for augmented reality applications in surgical simulation training’, Int J Med Robot Comput Assist Surg, 9(4):e34-51, 2013. Abstract

    • C. Loukas and E. Georgiou, ‘Surgical workflow analysis with Gaussian mixture multivariate autoregressive (GMMAR) models: a simulation study’, Comput Aided Surg, 18(3-4):47-62, 2013. Abstract

    • M.A. Kanakis, F.A. Mitropoulos, A.C. Chatzis and C. Loukas, ‘eComment. Coronary anastomosis simulation: assessing surgical dexterity’, Interact Cardiovasc Thorac Surg, 16(6):776-7, 2013. Abstract

    • M. Kanakis, A. Lioulias, G. Samanidis, C. Loukas and F. Mitropoulos, ‘Evolution in Experimental Fontan Circulation: A Review’, Ann Thorac Cardiovasc Surg, 19(3):177-85, 2013. Abstract

    • C. Loukas, ‘Assessment of tumour angiogenesis in tissue section images based on a self organizing map (SOM)’, Comput Methods Biomech Biomed Engin: Imaging & Visulization, 1(2), 111-118, 2013. Abstract

    • C. Loukaset al., ‘A head-to-head comparison between virtual reality and physical reality simulation training for basic skills acquisition‘, Surg Endosc, 26(9), 2550-8, 2012. Abstract

    • C. Loukas and P. Brown, ‘A PC-based system for predicting movement from deep brain signals in Parkinson’s disease’, Comp Meth Prog Biomed, 107(1):36-44, 2012. Abstract

    • C. Loukas, ‘Methods and tools for surgical assessment in the simulation world’, CyberTherapy & Rehabilitation, 4, 14-15, 2011. Abstract

    • C. Loukas and E. Georgiou, ‘Multivariate autoregressive modeling of hand kinematics for laparoscopic skills assessment of surgical trainees’, IEEE Trans Biomed Eng, 58(11), 3289-3297, 2011. Abstract

    • C. Loukaset al., ‘Evaluating the effectiveness of virtual reality simulation training in intravenous cannulation’, Simul Healthc, 6(4), 213-7, 2011. Abstract

    • C. Loukaset al., ‘The contribution of simulation training in enhancing key components of laparoscopic competence’, Am Surg, 77(6), 708-15, 2011. Abstract

    • C. Loukaset al., ‘Deconstructing laparoscopic competence in a virtual reality simulation environment’, Surgery, 149(6), 750-60, 2011. Abstract

    • C. Loukaset al., ‘A virtual reality simulation curriculum for intravenous cannulation training’, Acad Emerg Med, 7(10), 1142-5, 2010. Abstract

    • C.G. Loukas and A. Linney, ‘On a relaxation-labelling algorithm for quantitative assessment of tumour vasculature in tissue section images’, Comput Biol Med, 35(2), 157-171, 2005. Abstract

    • D. Williams, A. Kühn, A. Kupsch, M. Tijssen, G. van Bruggen, H. Speelman, G. Hotton, C. Loukas and P. Brown, ‘The relationship between oscillatory activity and motor reaction time in the parkinsonian subthalamic nucleus’, Eur J Neurosci., 21(1), 249-258, 2005. Abstract

    • L.H.A. Strens, P. Asselman, A. Pogosyan, C. Loukas, A. J. Thompson and P. Brown, ‘Cortico-cortical coupling in chronic stroke: it’s relevance to recovery’, Neurology, 63(3), 475-484, 2004. Abstract

    • L. Strens, R. Asselman, A. Pogosyan, C. Loukas, A. Thompson and P. Brown, ‘EEG-EEG connectivity changes after chronic stroke are correlated with functional recovery’, Neurology, 251, Suppl. 3, 74, 2004.

    • N. Fogelson, C. Loukas, J. Brown and P. Brown, ‘A common N400 EEG component reflecting contextual integration irrespective of symbolic form’, Clin Neurophysiol, 115(6), 1349-1358, 2004. Abstract

    • C. Loukas and P. Brown, ‘Online prediction of self-paced hand movements from subthalamic activity using neural networks in Parkinson’s disease’, J Neurosci Methods, 137(2), 193-205, 2004. Abstract

    • C.G. Loukas and A. Linney, ‘A survey on histological image analysis-based assessment of three major biological factors influencing radiotherapy: proliferation, hypoxia and vasculature’, Comput Methods Programs Biomed, 74(3), 183-199, 2004. Abstract

    • C.G. Loukas, G.D. Wilson. B. Vojnovic and A. Linney, ‘An image analysis-based approach for automated counting of cancer cell nuclei in tissue sections’, Cytometry, 55A(1), 30-42, 2003. Abstract

    • C.G. Loukas, G.D. Wilson, B. Vojnovic and A. Linney, ‘Tumour hypoxia and blood vessel detection – An image analysis technique for simultaneous tumour hypoxia grading and blood vessel detection in tissue sections’, Ann N Y Acad Sci, 980, 125-138, 2002. Abstract


    Recent International Conf. Proceedings

    • I. Seimenis, C. Loukas, et al., ‘Could textural analysis of MR images reduce overdiagnosis and overtreatment in prostate cancer?’, Int Conf Medical Physics, 2023, Mumbai India, Dec. 2023.

    • C. Loukas, et al., ‘A multiple-instance learning approach for the assessment of gallbladder vascularity from laparoscopic images’, In Proc. 15th Int. Joint Conf. Biomed. Engin. Syst. and Technol. (BIOSTEC), Vol. 2: Bioimaging, 15-23, online streaming event, Feb. 2022 (Best paper award). link1

    • C. Loukas and D. Schizas, ‘Assessment of gallbladder wall vascularity from laparoscopic images using deep learning’, In Proc. 13th Int. Joint Conf. Biomed. Engin. Syst. and Technol. (BIOSTEC), Vol. 2: Bioimaging, 28-36, Valletta, Malta, Feb. 2020. Paper

    • C. Loukas, ‘Surgical phase recognition of short video shots based on temporal modeling of deep features’, In Proc. 12th Int. Joint Conf. Biomed. Engin. Syst. and Technol. (BIOSTEC), Vol. 2: Bioimaging, 21-29, Prague, Czech Republic, Feb. 2019 (Best paper award). link1link2