利用广义正态分布优化全切片图像分割

K.P. Shivamurthy, Dr. Raju.A. S
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引用次数: 0

摘要

全切片图像(WSI)分割是帮助诊断肿瘤和癌细胞的一项重要任务。本文采用广义正态分布优化(GNDO)算法进行基于阈值的全切片图像分割。GNDO 算法利用广义正态分布的特性来确定图像分割的理想阈值。通过各种指标,证明了 GNDO 与传统大津阈值法相比的功效。结果表明,它能为不同的组织病理学图像提供可靠而灵活的解决方案。
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Optimal Whole Slide Image Segmentation Using Generalized Normal Distribution Optimization
Whole slide image (WSI) segmentation is a crucial task aiding tumour and cancerous cell diagnosis. Generalized Normal Distribution Optimization (GNDO) algorithm is adopted for whole slide image segmentation based on thresholding in this paper. GNDO algorithm utilizes the generalized normal distribution's properties to determine the ideal thresholds for image segmentation. Through various metrics, the efficacy of GNDO in comparison to traditional Otsu thresholding methods is demonstrated. As demonstrated by the results, it can offer reliable and flexible solutions for different histopathology images.
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