Early Classification of Brain Tumor Based on Image Histogram Using Fuzzy-Genetic Algorithm | ||||
| Fayoum University Journal of Engineering | ||||
| Article 8, Volume 4, Issue 1, November 2021, Page 166-174 PDF (570.47 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/fuje.2021.205140 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Tamer Barakat   ; Mai Elbadwey; Khaled H. Ibrahim
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| Electrical Engineering Department, Faculty of Engineering, Fayoum University | ||||
| Abstract | ||||
| A Brain Tumor Classification Framework has been outlined and created. The framework uses computer based strategies to identify tumor blocks or lesions and classify the sort of tumor utilizing matching histogram in MRI images of different patients with brain tumors. The picture processing methods such as picture segmentation, picture enhancement. Several techniques can classify the tumor such as Support vector machine (SVM), artificial neural networks (ANN), and Naive Bayes, but they did not accomplish the required accuracy. The automatic classification of tumors requires high precision since the non-accurate conclusion would cause a rise within the predominance of more serious diseases. In this paper, the proposed method using fuzzy logic and genetic algorithm based on image histogram to enhance the brain tumor classification. The experimental result showed that our technique is more effective than the previous techniques, as well as the classification accuracy efficiency is 99.9%. | ||||
| Keywords | ||||
| Image Segmentation; Histogram; MRI; Fuzzy; Membership and Weight | ||||
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