The Faculty of Computer Science and Information Technology discussed a master's thesis tagged segmentation of medical images using hybrid mass techniques based on machine learning algorithms, by the student Ahmed Ramadan Rashid, and supervised by Prof. Issa Ibrahim Issa, and, Dr. Burhan Fakhreddin Gomaa.The study aimed to demonstrate the importance of using the new technology (HMCSF) to remove noise from medical images taken by magnetic resonance MRI, segment them using hybrid Fuzzy C-means, and classify them using the SVM algorithm to diagnose tumors whether they are benign or malignant. The study concluded that the filtering method The new (HMCSF) is characterized by a high ability to remove noise in medical MRI images, and to maintain their quality. The hybrid Fuzzy C-means algorithm has a higher accuracy for tumor segmentation compared to the Fuzzy C-means algorithm
K-means, as well as the SVM algorithm, has superior ability to classify tumors