Thayumanavan Meenal, Ramasamy Asokan
Department of Electronics and Communication Engineering, Kongunadu College of Engineering and Technology, Trichy, Tamilnadu, India.
Network. 2025 Aug;36(3):688-715. doi: 10.1080/0954898X.2024.2343340. Epub 2024 Apr 22.
Brain tumour can be cured if it is initially screened and given timely treatment to the patients. This proposed idea suggests a transform- and windowing-based optimization strategy for exposing and segmenting the tumour region in brain pictures. The processes of image processing that are included in the proposed idea include preprocessing, transformation, feature extraction, feature optimization, classification, and segmentation. In order to convert the pixels connected to the spatial domain into a multi-resolution domain, the Gabor transform is first applied to the brain test image. The Gabor converted brain image is then used to extract the parameters of the multi-level features. After that, the Genetic Algorithm (GA) is used to optimize the extracted features, and Neuro Fuzzy System (NFS) is used to classify the optimistic prominent section. Finally, the tumour region in brain images is found and segmented using the normalized segmentation algorithm. The effective detection and classification of brain tumours by the characteristics of sensitivity, specificity, and accuracy are described by the suggested GA-based NFS classification approach. The trial findings are displayed with an average of 99.37% sensitivity, 98.9% specificity, 99.21% accuracy, 97.8% PPV, 91.8% NPV, 96.8% FPR, and 90.4% FNR.
如果对脑肿瘤患者进行初步筛查并及时给予治疗，脑肿瘤是可以治愈的。这个提议的想法提出了一种基于变换和窗口化的优化策略，用于在脑部图像中暴露和分割肿瘤区域。该提议想法中包含的图像处理过程包括预处理、变换、特征提取、特征优化、分类和分割。为了将连接到空间域的像素转换为多分辨率域，首先将伽柏变换应用于脑部测试图像。然后使用伽柏变换后的脑部图像提取多级特征的参数。之后，使用遗传算法（GA）对提取的特征进行优化，并使用神经模糊系统（NFS）对优化后的突出部分进行分类。最后，使用归一化分割算法找到并分割脑部图像中的肿瘤区域。所提出的基于GA的NFS分类方法描述了通过灵敏度、特异性和准确性特征对脑肿瘤进行有效的检测和分类。试验结果显示，平均灵敏度为99.37%，特异性为98.9%，准确性为99.21%，阳性预测值为97.8%，阴性预测值为91.8%，假阳性率为96.8%，假阴性率为90.4%。
