Machine Learning Methods for Microwave Imaging in Cancer Detection
Author:
Affiliation:
1. University of Calabria,Department of Computer Engineering, Modeling, Electronics and Systems,Rende,Italy,87036
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9927523/9927699/09927985.pdf?arnumber=9927985
Reference21 articles.
1. High-Resolution Microwave Breast Imaging Using a 3-D Inverse Scattering Algorithm With a Variable-Strength Spatial Prior Constraint
2. The contrast source inversion method for location and shape reconstructions
3. Artificial Intelligence: New Frontiers in Real-Time Inverse Scattering and Electromagnetic Imaging
4. Microwave Imaging of the Neck by Means of Artificial Neural Networks for Tumor Detection
5. Conventional Machine Learning versus Deep Learning for Magnification Dependent Histopathological Breast Cancer Image Classification: A Comparative Study with Visual Explanation
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1. Microwave Imaging for Brain Cancer Detection: Enhanced Accuracy with Machine Learning Approach;2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE);2023-10-25
2. Segmentation Approach for Enhanced Biomedical Microwave Imaging;2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE);2023-10-25
3. Machine Learning Architectures for Microwave Imaging with Enhanced Reconstruction;2023 24th International Conference on Applied Electromagnetics and Communications (ICECOM);2023-09-27
4. Machine Learning Approach to Enhanced Resolution of Inverse Scattering for Cancer Detection;2023 Photonics & Electromagnetics Research Symposium (PIERS);2023-07-03
5. Fast and Accurate CNN-Based Machine Learning Approach for Microwave Medical Imaging in Cancer Detection;IEEE Access;2023
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