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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Ahmed Adel Ismail
The Higher Institute of Computer and Information Systems
Computer Science & IT Engineering

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Automatic brain tumor detection using adaptive region growing with thresholding methods Kadry Ali Ezzat; Lamia Nabil Omran; Ahmed Adel Ismail; Ahmed Ibrahim Bahgat El Seddawy
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v12.i4.pp1569-1576

Abstract

Brain cancer affects many people around the world. It's not just limited to the elderly; it is also recognized in children. With the development of image processing, early detection of mental development is possible. Some designers suggest deformable models, histogram averaging, or manual division. Due to constant manual intervention, these cycles can be uncomfortable and tiring. This research introduces a high-level system for the removal of malignant tumors from attractive reverberation images, based on a programmed and rapid distribution strategy for surface extraction and recreation for clinicians. To test the proposed system, acquired tomography images from the Cancer Imaging Archive were used. The results of the study strongly demonstrate that the intended structure is viable in brain tumor detection.
Co-Authors Ahmed Ibrahim Bahgat El Seddawy Kadry Ali Ezzat Lamia Nabil Omran