基于分割的异型红细胞增多症检测方法

G. N, A. S, D. S, Akilan R, Fayaz A
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引用次数: 0

摘要

手工检测镰状细胞不是不可能的工作,但它是一个繁琐的图像处理应用。它包括通过检测细胞来分析细胞,以确定疾病并进行适当的治疗。通过对镰状细胞进行适当的分割,我们可以准确地检测镰状细胞。因为我们研究的是细胞形态的结构框架它在分离镰状细胞和健康血细胞中起着至关重要的作用它们在结构完整性上是不同的。这将大大加快分离和鉴定镰状细胞在健康的人类血细胞。采用标准的验证策略来提高各种方法的性能和收率。通过该模型对本文所采用的方法和技术进行了研究和分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of Poikilocytosis using Segmentation based Approach
Detecting a sickle cell manually is not an impossible job but it is a tedious one where the image processing is applied. It involves the analysis of cells by detecting the cells to identify the disease for proper treatment. We can make accurate detection of sickle cells by conducting a proper segmentation of such cells. Since we are dealing with the structural framework of the cell morphology which plays a crucial part in separating sickle cells from healthy blood cells and they differ from each other by structural integrity. This will substantially speed up the segregation and identification of sickle cells in healthy human blood cells. Standard validation strategies are adopted to improve the performance and yield of various methods. The methodology and techniques used in this paper are investigated and analyzed through this model.
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