| 范胜男,邓君,张子扬,阮健磊,潘艳,孙全富.基于人工智能的双着丝粒染色体识别算法初步研究[J].中华放射医学与防护杂志,2022,42(5):343-347 |
| 基于人工智能的双着丝粒染色体识别算法初步研究 |
| Preliminary study on dicentric chromosome identification algorithm based on artificial intelligence technology |
| 投稿时间：2021-12-13 |
| DOI：10.3760/cma.j.cn112271-20211213-00480 |
| 中文关键词: 双着丝粒染色体 生物剂量估算 人工智能 模糊逻辑 自动识别 |
| 英文关键词:Dicentric chromosome Biodosimetry Artificial intelligence Fuzzy logic Automatic Identification |
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| 摘要点击次数: 1624 |
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| 中文摘要: |
| 目的 为解决双着丝粒染色体人工分析费时费力的问题,探索人工智能技术,提出一种实现双着丝粒染色体自动识别的算法,从而实现快速高通量生物剂量估算。方法 结合人工智能和图像处理技术,基于MATLAB软件,通过研究图像预处理、阈值分割、二值化处理、区域标识、卷积神经网络和双着丝点识别算法,定义模糊隶属度函数来描述每条染色体属于双着丝粒染色体的程度,设定判别阈值,实现双着丝粒染色体自动识别。结果 通过对1 471张染色体图像进行算法检验,与人工识别相比,双着丝粒染色体细胞检出率达到了70.7%。结论 本算法对双着丝粒染色体自动识别进行了初步研究,并达到了较好的效果。 |
| 英文摘要: |
| Objective To explore artificial intelligence technology and propose an algorithm for automatic identification of dicentric chromosomes to realize fast and high-throughput biodosimetry. In order to solve the time-consuming and laborious problem of manual analysis of dicentric chromosomes.Methods Combining artificial intelligence technology and image processing technology, based on MATLAB software, algorithms like image preprocessing, threshold segmentation algorithm, binarization processing, area identification algorithm, convolutional neural network algorithm and double centripetal recognition algorithm were applied. A fuzzy membership function was defined to describe the degree of each chromosome belonging to a dicentric chromosome, and the discrimination threshold was set to realize the automatic identification of dicentric chromosomes.Results Through the test on 1 471 chromosome images, compared with manual recognition, the detection rate of dicentric chromosomes cells of this algorithm reached 70.7%.Conclusions This algorithm method carries out a preliminary study on the automatic identification of dicentric chromosomes with good result. |
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