Chair and Organizer

Prof. Dr. Abdel-Badeeh M. Salem
Prof. of Computer Science, Faculty of Computer and Information Sciences,
Head of Artificial Intelligence and Knowledge Engineering Research Labs,
Ain Sham University, Egypt,
Coordinator of Medical and Bio-Informatics Working Group,
International Society for Telemedicine&eHealth, ISfTeH, Belgium,

Workshop Presentation

With advances in Computational Intelligence (CI) and Machine Learning (ML) techniques, computer-aided detection attracts more attention for brain tumor detection. It has become one of the major research subjects in medical imaging and diagnostic radiology. CI and ML have become of significant importance for extracting meaningful relationships and making accurate prediction in many fields. In the area of processing the brain images, Computer Aided-Diagnosis (CAD) systems basically rely on different ML techniques within all stages to implement a system that can help radiologists by detect and diagnose brain tumors based on imaging techniques widely used in clinical care. Magnetic Resonance Imaging (MRI) is an imaging technique that plays a vital role in the detection and diagnosis of brain tumors in both research and clinical care for providing detailed information about the brain structure and its soft tissues.

This workshop is devoted towards presenting the state-of-the-art AI techniques and knowledge engineering methodologies for developing intelligent CAD Systems. The goal is to provide a forum for the exchange of ideas between practitioners from neuroscience, cognitive science, medicine, and computer science, and knowledge engineering to address the important issues in those areas. Papers related to methodologies, techniques and applications in brain informatics, telemedicine, and neuro-imaging technologies are especially solicited.

The topics of interest include, but are not limited to:

  • AI-based techniques for developing CAD systems
  • AI-based techniques for brain imaging
  • MRI image acquisition and preprocessing
  • Intelligent segmentation techniques
  • Intelligent feature extraction approaches
  • Predicting brain tumors using Deep Neural Networks
  • Intelligent classification techniques
  • Pattern recognition techniques
  • Artificial neural network-based classifiers
  • Classification of Brain MRI to predict Alzheimer

Organizing Committee

  • Abdel-Badeeh M. Salem, Faculty of Computer and Information Sciences, Ain Sham University, Egypt
  • Frank Lievens, International Society for Telemedicine & eHealth, ISfTeH, Belgium
  • Francesco Sicurello, University of Milan Bicocca, Italy

Program Committee

  • Roumen Kountchev, Technical University of Sofia, Bulgaria
  • Amer Goneid, Computer Science Dept., American University in Cairo, Egypt
  • Mohamed Roushdy, Ain Shams University, Egypt
  • Livia Bellina, Global Health Work Force Alliance, Palermo, Italy
  • YukakoYagi, Harvard Medical School, Boston, MA, USA
  • Hariton Costin, “Gr. T. Popa” Univ of Medicine and Pharmacy, Romania
  • Smaranda Belciug, Faculty of Mathematics and Natural Sciences, University of Craiova, Romania
  • Hassan Ghazal, Moroccan Society for Telemedicine and eHealth, Morocco
  • Antoanela Naaji, "VasileGoldis" Western University of Arad, Romania
  • Nouhad Rizk, Computer Science Department, University of Houston, USA
  • Roumiana Kountcheva, T&K Engineering Co.,Sofia, Bulgaria
  • Dina Ziadlou, Doctoral Management-Healthcare management and leadership, Colorado Technical University, USA
  • Klimis Ntalianis, University of West Attica, Agiou Spyridones, Athens, Greece
  • EL-Sayed A. El-Dahshan, Egyptian E-Learning University, Cairo, Egypt
  • Valérie Monfort, Univ. Paris1 Panthéon Sorbonne, France
  • David OlatayoOlayiwola, University College Hospital, Ibadan,Nigeria
  • Ram Prakash Suriyanarayanan, Institute of Technology, European Campus Rottal Inn, Pfarrkirchen, Germany
  • Nechita Elena, “Vasile Alecsandri” University of Bacau, Romania
  • Anna Stoynova, Center for High Technological Solutions in Electronics, Technical University, Sofia, Bulgaria
  • Marco Alfonse, Ain Shams University, Egypt
  • Wael Khalifa, Ain Shams University, Egypt
  • Giovanna Castellano, University of Bari Aldo Moro, Italy

Important Dates

  • September 15, 2018: Submission Deadline
  • October 5, 2018: Author Notification
  • December 7, 2018: Workshops & Special Sessions
  • December 8-9, 2018: Main Conference

Submission URL:

Full-paper submissions should be limited to a maximum of 10 pages including figures and references, while high quality paper submissions with up to 6 pages are also welcome and will be accepted as short papers based on their originality, significance of contribution to the field, technical merit, and presentation quality.
All paper submissions should follow Springer LNCS Proceedings format.