B-MIPT: A Case Tool for Biomedical Image Processing and Their Classification Using Nearest Neighbor and Genetic Algorithm

Pardeep Kumar Naik, N. Nitin, A. Janmeja, Sushain Puri, Kunal Chawla, Manav Bhasin, Kunal Jain
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引用次数: 2

Abstract

A high rate of expression of Endothelin protein in the placental cell is very much regulated by inhalation of tobacco smoke and leads to placental abnormalities subjected to birth failure. Our application developed using Image Processing [1-7], Nearest Neighbor algorithm (NN) and Genetic Algorithms (GA) [8-12], automates the study of these proteins to assist pathologists and lab technicians in achieving a more efficient and faster diagnosis. Using three distinct parameters, recognition of images with high protein expression was accurate up to 91% of the times. The tool has achieved a Matthews Correlation Coefficient (MCC) of 0.91. Other performance measures are = 91.1%, sensitivity = 0.91 and specificity = 0.82. These showed that computer aided diagnosis can be a helpful tool, especially in a field that lacks experienced specialists.
B-MIPT:生物医学图像处理与遗传算法分类的案例工具
胎盘细胞中内皮素蛋白的高表达率在很大程度上受吸入烟草烟雾的调节,并导致胎盘异常,导致出生失败。我们的应用程序使用图像处理[1-7]、最近邻算法(NN)和遗传算法(GA)[8-12]开发,使这些蛋白质的研究自动化,以帮助病理学家和实验室技术人员实现更高效、更快速的诊断。使用三个不同的参数,对高蛋白表达图像的识别准确率高达91%。该工具的马修斯相关系数(MCC)为0.91。其他性能指标= 91.1%,敏感性= 0.91,特异性= 0.82。这些研究表明,计算机辅助诊断是一种有用的工具,特别是在缺乏经验丰富的专家的领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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