School of Computing, DIT University, Dehradun, India.
Department of Industrial and Technology Management, Faculty of Management and Economy, Islamic Azad University, Science and Research Branch, Tehran, Iran.
Comput Intell Neurosci. 2022 May 11;2022:5465279. doi: 10.1155/2022/5465279. eCollection 2022.
Medical image segmentation is a technique for detecting boundaries in a 2D or 3D image automatically or semiautomatically. The enormous range of the medical image is a considerable challenge for image segmentation. Magnetic resonance imaging (MRI) scans to aid in the detection and existence of brain tumors. This approach, however, requires exact delineation of the tumor location inside the brain scan. To solve this, an optimization algorithm will be one of the most successful techniques for distinguishing pixels of interest from the background, but its performance is reliant on the starting values of the centroids. The primary goal of this work is to segment tumor areas within brain MRI images. After converting the gray MRI image to a color image, a multiobjective modified ABC algorithm is utilized to separate the tumor from the brain. The intensity determines the RGB color generated in the image. The simulation results are assessed in terms of performance metrics such as accuracy, precision, specificity, recall, F-measure, and the time in seconds required by the system to segment the tumor from the brain. The performance of the proposed algorithm is computed with other algorithms like the single-objective ABC algorithm and multiobjective ABC algorithm. The results prove that the proposed multiobjective modified ABC algorithm is efficient in analyzing and segmenting the tumor from brain images.
医学图像分割是一种自动或半自动检测二维或三维图像边界的技术。医学图像的巨大范围对图像分割来说是一个相当大的挑战。磁共振成像 (MRI) 扫描有助于检测和发现脑肿瘤。然而，这种方法需要精确地描绘出脑扫描中肿瘤的位置。为了解决这个问题，优化算法将是区分感兴趣像素与背景的最成功技术之一，但它的性能依赖于质心的起始值。这项工作的主要目标是分割脑 MRI 图像中的肿瘤区域。将灰度 MRI 图像转换为彩色图像后，使用多目标改进的 ABC 算法将肿瘤与大脑分离。强度决定了图像中生成的 RGB 颜色。模拟结果根据性能指标进行评估，如准确性、精度、特异性、召回率、F 度量和系统分割肿瘤所需的时间（以秒为单位）。还计算了与其他算法（如单目标 ABC 算法和多目标 ABC 算法）的比较性能。结果证明，所提出的多目标改进的 ABC 算法在分析和分割脑肿瘤图像方面是有效的。
