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首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >Modified histogram-based segmentation and adaptive distance tracking of sperm cells image sequences
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Modified histogram-based segmentation and adaptive distance tracking of sperm cells image sequences

机译：基于直方图的基于直方图的细胞图像序列的分割和自适应距离跟踪

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摘要

Abstract Proper recognition and tracking of microscopic sperm cells in video images are vital steps of male infertility diagnosis and treatment. The segmentation and detection of sperms in microscopic image analysis is a complicate process as a result of their small sizes, fast movements, and considerable collisions. Histogram-based thresholding schemes are very popular for this purpose, since they are quite fast and provide almost acceptable results. This paper proposes a combined method for sperm cells detection, which consists of a non-linear pre-processing stage, a histogram-based thresholding algorithm, and a tracking method based on an adaptive distance scheme. The results of conducted experiments verify the superiority of the proposed scheme with incorporated Kittler algorithm compared to the other competitive methods in the majority of cases.
机译：摘要在视频图像中的正确识别和跟踪微观精子细胞是男性不孕症诊断和治疗的重要步骤。 微观图像分析中精子的分割和检测是由于它们的小尺寸，快速运动和相当大的碰撞而复杂的过程。 基于直方图的阈值方案为此目的非常流行，因为它们非常快，并且提供几乎可接受的结果。 本文提出了一种用于精子细胞检测的组合方法，其包括非线性预处理阶段，基于直方图的阈值算法和基于自适应距离方案的跟踪方法组成。 进行实验的结果验证了与大多数情况下的其他竞争方法相比纳入Kittler算法的提出方案的优势。

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