عنوان المقالة:تعزيز جودة الصورة الطبية باستخدام المجال الضبابي النيوتروسوفيكي وتحويلات التعزيز متعددة المستويات: دراسة مقارنة للكشف عن سرطان الدم وتصنيفه Enhancing Medical Image Quality using Neutrosophic Fuzzy Domain and Multi-Level Enhancement Transforms: A Comparative Study for Leukemia Detection and Classification
A. A.Salama, Mahmoud Y.Shams, Huda E. Khalid, Doaa E.Mousa
Abstract
Medical image processing has become a critical research area due to the vast amounts of
digital image data available. However, medical images often suffer from poor illumination and low
visibility of significant structures, requiring image enhancement to improve image quality before
processing. In this paper, we propose a technique for enhancing medical images by removing noise
and improving contrast based on three different enhancing transforms. The proposed technique
embeds the image into a neutrosophic fuzzy domain, where it is mapped into three different levels
of trueness, falseness, and indeterminacy, and each level is processed individually using the
enhancement transforms. We compare the proposed technique with four other systems for leukemia
detection and classification using accuracy and T, I, and F values. The proposed system performs
the best with an accuracy of 98%, outperforming the other systems in terms of accuracy, degree of
indeterminacy, and falsity. The proposed system uses different algorithms and filters to process
images and extract features like color and texture. The system's classification uses k-means for
segmentation and SVM for classification. The paper highlights the importance of considering T, I,
and F values in evaluating the performance of different systems for leukemia detection and
classification, providing a more accurate representation of the uncertainty and ambiguity involved
in the evaluation process.
أ.د. أحمد سلامة | Prof. Dr. Ahmed Salama | 10221