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An automated approach to detect human ovarian tissues using type P63 counter stained histopathology digitized color images

机译:使用P63型计数器染色的组织病理学数字化彩色图像检测人卵巢组织的自动化方法

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The human ovary contains a fixed number of reproductive tissues at birth. This number decreases with age which leads to complications in conceiving. As part of the medical consultation process and to know the actual condition of a female ovary, manual microscopic routine examination is carried out by pathology experts. Laboratory expert manual microscopic analysis is time consuming and prone to errors. To minimize labor cost and time associated with manual analysis an ultrasound technique is commonly used. This ultrasound technique can only identify larger and more mature tissues rather than small ovarian tissues. To analyze small ovarian reproductive tissues accurately a fully automated approach is proposed in this paper to assist pathology experts. The proposed method processes digitized color histopathology images acquired from biopsy slide and identifies ovarian reproductive tissues automatically. The study's experimental results indicate excellent performance in terms of accuracy.
机译:人卵巢在出生时含有固定数量的生殖组织。这个数字随着年龄的增长而减少,这导致受孕的复杂化。作为医学咨询过程的一部分,并且为了了解雌性卵巢的实际状况,病理专家会进行手动显微例行检查。实验室专家的手动显微分析非常耗时且容易出错。为了使与人工分析相关的人工成本和时间最小化,通常使用超声技术。这种超声技术只能识别更大,更成熟的组织,而不能识别小的卵巢组织。为了准确地分析卵巢小生殖组织,本文提出了一种全自动方法来协助病理学专家。所提出的方法处理从活检玻片获取的数字化彩色组织病理学图像,并自动识别卵巢生殖组织。该研究的实验结果表明,在准确性方面表现出色。

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