Utilization of image interpolation and fusion in brain tumor segmentation

Author:

El‐Hag Noha A.1ORCID,Sedik Ahmed2ORCID,El‐Banby Ghada M.3ORCID,El‐Shafai Walid45ORCID,Khalaf Ashraf A. M.1ORCID,Al‐Nuaimy Waleed6ORCID,Abd El‐Samie Fathi E.47ORCID,El‐Hoseny Heba M.8ORCID

Affiliation:

1. Department of Electronics and Electrical Communications, Faculty of Engineering Minia University Minya Egypt

2. Department of Robotics and Intelligent Machines, Faculty of Artificial Intelligent Kafr Elsheikh University Kafr el‐Sheikh Egypt

3. Department Industrial Electronics and Control Engineering, Faculty of Electronic Engineering Menoufia University Menouf Egypt

4. Department of Electronics and Electrical Communications, Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt

5. Security Engineering Lab, Computer Science Department, Prince Sultan University Riyadh Saudi Arabia

6. Department of Electrical and Electronic Engineering University of Liverpool Liverpool UK

7. Department of Information Technology College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University Riyadh Saudi Arabia

8. Department of Electronics and Electrical Communication Engineering Al‐Obour High Institute for Engineering and Technology Al Obour Egypt

Publisher

Wiley

Subject

Applied Mathematics,Computational Theory and Mathematics,Molecular Biology,Modelling and Simulation,Biomedical Engineering,Software

Reference37 articles.

1. https://mayfieldclinic.com/pe-braintumor.htm.

2. https://www.nibib.nih.gov/science-education/science-topics/magnetic-resonance-imaging-mri.

3. https://www.healthline.com/health/ct-scan.

4. Various image segmentation techniques: a review;Kaur D;Int J Comput Sci Mobile Comput,2014

5. Automatic brain tumor segmentation from MRI using greedy snake model and fuzzy C‐means optimization;Sheela CJJ;J King Saud Univ ‐ Comput Inf Sci,2019

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