Automated chromosomes counting systems using deep neural network

被引：0
|
作者：
Kang, Seungyoung [1 ]
Han, Junghun [1 ]
Chu, Yuseong [1 ]
Lee, Inkyung [2 ]
Joo, Haemi [2 ]
Yang, Sejung [1 ]
机构：
[1] Yonsei Univ, Dept Biomed Engn, Wonju, South Korea
[2] Korea Hydro & Nucl Power, Radiat Hlth Inst, Seoul, South Korea
来源：
2022 INTERNATIONAL CONFERENCE ON ELECTRONICS, INFORMATION, AND COMMUNICATION (ICEIC) | 2022年
关键词：
Deep Learning; Object detection; Chromosome;
D O I：
10.1109/ICEIC54506.2022.9748307
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Karyotyping analysis is an important clinical process used in the process of diagnosing several genetic diseases by analyzing the number or shape of chromosomes. If the number of chromosomes is out of the normal range, it can cause hereditary diseases such as Down syndrome and Edward syndrome. In this study, we employed Faster R-CNN-based model for automated chromosome counting systems and showed a result of 0.914 in average precision [IoU = 0.75]. As a result, it was possible to count chromosomes by detecting each object with a high probability for independent and overlapping chromosomes.
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收藏
页数：3
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