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Home / Journals / International Journal of Biomedical Engineering and Clinical Science / Biomedical Signal & Image Processing and Pattern Recognition
Biomedical Signal & Image Processing and Pattern Recognition

Special Issue Flyer (PDF)

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Lead Guest Editor:
Ali Momennezhad
Department of Biomedical Engineering Sahand University of Technology, Sahand, Tabriz, Iran
Guest Editors
Nivedita Daimiwal
Sathyabama University
Chennai, Tamil Nadu, India
Revati Shriram
Cummins College of Engineering for Women
Pune, Maharashtra, India
Hamid Hassanpour
Shahrood University of Technology
Semnan, Shahrood, Iran
Eric Laciar Leber
Sanjuan University
San Juan, Argentina
Sajib Saha
University of New south Wales
Kensington, Sydney, Australia
Rajib Rana
University of Southern Queensland
Queensland, Australia
The suggested issue title aims to attract papers on physiological signal and Image processing like EEG, EMG, ECG, EOG, MRI etc. and their applications in bringing more comfort to, specifically, the life of the disabled, patients suffering cancers, Tumors and etc. As it is known, scholars in these fields are facing many problems. For example, in EEG, patients usually have to wear a cap with too many electrodes which makes it very annoying and uncomfortable. Also, the proposed algorithms usually are restricted to laboratories not real life. So, user-friendly and accurate techniques are needed to satisfy the demands in the world outside the labs. Physiological signals (Images) are naturally noisy and have low signal to noise ratio (SNR) and it is almost the major problem in the mentioned fields. Also, physiological data are usually large in quality as well as noise. For solving these challenges and problems, fast, robust, more efficient, accurate and cutting-edge pattern recognition methods are required to process these raw signals& images.
Also, in order to advance further in these fields, studies on the structure and performance of the brain, Eye, Heart and muscles are required. Through deep knowledge of the structure of the body, scholars can acquire more authentic, efficient and reliable data-set and suggest more effective methods.

Aims and Scope:

  1. Brain, Heart, Eye, Muscle Morphology
  2. EEG
  3. Classification
  4. Feature Extraction
  5. Signal & Image Processing
  6. Feature Selection
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