Diagnostic Imaging Systems

Dr. El-Baz is a Professor, University Scholar, and Chair of the Bioengineering Department at the University of Louisville, KY. Dr. El-Baz earned his bachelor's and master’s degrees in Electrical Engineering in 1997 and 2001, respectively. He earned his doctoral degree in electrical engineering from the University of Louisville in 2006. In 2009, Dr. El-Baz was named a Coulter Fellow for his contributions to the field of biomedical translational research. Dr. El-Baz has 15 years of hands-on experience in the fields of bio-imaging modeling and non-invasive computer-assisted diagnosis systems. He has authored or coauthored more than 450 technical articles (105 journals, 15 books, 50 book chapters, 175 refereed-conference papers, 100 abstracts, and 15 US patents). Dr. Jasjit Suri, PhD, MBA, is a renowned innovator and scientist. He received the Director General’s Gold Medal in 1980 and is a Fellow of several prestigious organizations, including the American Institute of Medical and Biological Engineering and the Institute of Electrical and Electronics Engineers. Dr. Suri has been honored with lifetime achievement awards from Marcus, NJ, USA, and Graphics Era University, India. He has published nearly 300 peer-reviewed AI articles, 100 books, and holds 100 innovations/trademarks, achieving an H-index of nearly 100 with about 43,000 citations. Dr. Suri has served as chairman of AtheroPoint, IEEE Denver section, and as an advisory board member to various healthcare industries and universities globally.

• 1. Artificial Intelligence in Diagnostic Imaging for Modern Medicine2. Yolo-Based Detection and Segmentation: Advancing Real-Time AI in Medical Imaging3. Breast Cancer Prediction using Image Processing on Big Data: An Empirical Study for Sustainable Health in 21st Century Lifestyle4. Segmentation and Classification Techniques using AI and their State-of-the-art for the Human Brain Magnetic Resonance Images (MRI)5. Efficient Artificial Intelligence Techniques for Brain Tumor Classification: Comprehensive Review and Analysis6. A Novel Cell Nuclei Semantic Segmentation Network for Childhood Medulloblastoma Histopathological Images7. Exploring AI Innovations for Enhanced Brain Tumor Imaging and Diagnosis8. Radioengineering Approach for Brain Activity Restoration after Trauma9. Comparative Analysis of Fast Fuzzy C-Means and Kernel Fuzzy C-Means Algorithms for 3D Brain Tumor Segmentation on the BraTS MICCAI 2021 Dataset10. SwinUNet Plus: An Adaptive Hierarchical Attention Network for Endoscopic Image Segmentation11. A YOLO-Based Model for Brain Tumor Detection in Magnetic Resonance Imaging Scans12. ECG Classification Based CNN Neural Network Models for Arrhythmia Detection13. Classification of Brain Tumors using AI and Radiomics Techniques

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