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Home / Journals / International Journal of Systems Engineering / Recent Trends in Machine Intelligence in Medical Imaging
Recent Trends in Machine Intelligence in Medical Imaging
Lead Guest Editor
Dr. Paulchamy Balaiyah
Department of Electronics and Communication, Hindusthan Educational Institutions, Coimbatore, India
Guest Editors
  • Dr. Arun Kumar Sivaraman
    Department of Computer Science Engineering, Vellore Institute of Technology, Chennai, India
  • Dr. Suresh Babu
    Department of Electronics and Communication, Hindusthan Institute of Technology, Coimbatore, India
  • Vairaprakash S.
    Department of Electronics, Anna University, Chennai, India
  • Dr. Mujahid Tabassum
    IT, University of Technology and Applied Science, Muscat, Oman
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Special Issue Information
With the beginning of the Medical imaging epoch, conventional geometric algorithms face various challenges in segmentation and classification of the diseased region from a massive amount of data. Current Imaging techniques generate a great deal of data stored in medical databases. Clinical databases can be categorized as big data and include large quantities of information about patients and their medical conditions.
Analyzing the Stages and Features of diseases in clinical database images in addition to discovering relationships among a massive number of the database using Segmentation and Classification techniques could unveil hidden medical knowledge and brings changes in clinical diagnosis. Because medical information has the characteristics of idleness, multi-attribution, incompletion, and is closely related to time, medical imaging techniques may differ.
This Special Issue seeks original, high-quality contributions that present novel medical imaging approaches. Original research and review articles are welcome.
Aims and Scope:
  1. Medical Imaging and Knowledge Discovery in Disease Classification
  2. Medical Imaging Process Analysis Expert Systems
  3. Medical Knowledge Engineering
  4. Segmentation And Classification Algorithm in Medical Imaging
  5. Optimization in Segmentation and Classification in Medical Imaging
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