枚举
计算机科学
染色体
中期
卷积神经网络
模式识别(心理学)
人工智能
核型
人工神经网络
算法
数学
生物
遗传学
基因
组合数学
作者
Li Xiao,Chen Luo,Yong Luo,Tianqi Yu,Chan Tian,Jie Qiao,Yi Zhao
标识
DOI:10.1007/978-3-030-32239-7_66
摘要
Chromosome enumeration is an important but tedious procedure in karyotyping analysis. In this paper, to automate the enumeration process, we developed a chromosome enumeration framework, DeepACE, based on the region based object detection scheme. Firstly, the ability of region proposal network is enhanced by a newly proposed Hard Negative Anchors Sampling to extract unapparent but important information about highly confusing partial chromosomes. Next, to alleviate serious occlusion problems, we novelly introduced a weakly-supervised mechanism by adding a Template Module into classification branch to heuristically separate overlapped chromosomes. The template features are further incorporated into the NMS procedure to further improve the detection of overlapping chromosomes. In the newly collected clinical dataset, the proposed method outperform all the previous method, yielding an mAP with respect to chromosomes as 99.45, and the error rate is about 2.4%.
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