Preliminary study on dicentric chromosome identification algorithm based on artificial intelligence technology
10.3760/cma.j.cn112271-20211213-00480
- VernacularTitle:基于人工智能的双着丝粒染色体识别算法初步研究
- Author:
Shengnan FAN
1
;
Jun DENG
;
Ziyang ZHANG
;
Jianlei RUAN
;
Yan PAN
;
Quanfu SUN
Author Information
1. 中国疾病预防控制中心辐射防护与核安全医学所，北京 100088
- Keywords:
Dicentric chromosome;
Biodosimetry;
Artificial intelligence;
Fuzzy logic;
Automatic Identification
- From:
Chinese Journal of Radiological Medicine and Protection
2022;42(5):343-347
- CountryChina
- Language:Chinese
-
Abstract:
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.
