Segmentation Of Biological Cells In Microscopic Images

Sai Teja Kolipaka, Arush Karingala, Sandeep Reddy Lingala, Mohammed Ayub Ashraf, K. Manisha
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Abstract

Image analysis of cells is an important aspect for research in biomedical applications. Image segmentation is the important step in image analysis. The task is not so easy as to identify the cells as there a lot of complexities like the removal of background noise, overlapping of cells, and change in the position of the cell. This paper examines and analyses various methods for pre-processing and segmentation using metrics, which are used to study the shape, size and behavior of the cells. First step is the pre-processing to reduce the noise present in the image. Then the pre-processed image is taken as the input and the cells in the image are segmented. The compared results of various techniques by measuring the accuracy, Jaccard index and number of cells detected in the image.
显微图像中生物细胞的分割
细胞图像分析是生物医学研究的一个重要方面。图像分割是图像分析的重要步骤。这项任务并不像识别细胞那么简单,因为有很多复杂的问题,如去除背景噪声、细胞重叠、细胞位置变化等。本文研究和分析了各种预处理和分割的方法,使用度量来研究细胞的形状、大小和行为。第一步是预处理,以减少图像中存在的噪声。然后将预处理后的图像作为输入,对图像中的细胞进行分割。通过测量精度、Jaccard指数和图像中检测到的细胞数,比较了不同技术的检测结果。
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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