Segmentation of Drosophila heart in optical coherence microscopy images using convolutional neural networks.
Segmentation of Drosophila heart in optical coherence microscopy images using convolutional neural networks.
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DOI：
10.1002/jbio.201800146
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发表时间：
2018-12
影响因子：
2.8
通讯作者：
Zhou C
中科院分区：
文献类型：
--
作者：
Duan L;Qin X;He Y;Sang X;Pan J;Xu T;Men J;Tanzi RE;Li A;Ma Y;Zhou C
Convolutional neural networks are powerful tools for image segmentation and classification. Here, we use this method to identify and mark the heart region of Drosophila at different developmental stages in the cross-sectional images acquired by a custom optical coherence microscopy (OCM) system. With our well-trained convolutional neural network model, the heart regions through multiple heartbeat cycles can be marked with an intersection over union (IOU) of ~86%. Various morphological and dynamical cardiac parameters can be quantified accurately with automatically segmented heart regions. This study demonstrates an efficient heart segmentation method to analyze OCM images of the beating heart in Drosophila. Convolutional neural networks are powerful tools for image segmentation and classification. In this paper, a neural network is built to identify and mark the heart region of Drosophila images acquired optical coherence microscopy (OCM) system. By building and training the neural network, we successfully achieved high accuracy of prediction in terms of intersection of union (IOU), and various morphological and dynamical cardiac parameters can be quantified accurately with automatically segmented heart regions.
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影响因子：
3.7
作者：
Alex A;Li A;Zeng X;Tate RE;McKee ML;Capen DE;Zhang Z;Tanzi RE;Zhou C
通讯作者：
Zhou C
影响因子：
10.5
作者：
AZPIAZU, N;FRASCH, M
通讯作者：
FRASCH, M
影响因子：
5.7
作者：
Chang, Herng-Hua;Zhuang, Audrey H.;Chu, Woei-Chyn
通讯作者：
Chu, Woei-Chyn
影响因子：
4.8
作者：
Burges, CJC
通讯作者：
Burges, CJC
影响因子：
3.5
作者：
Drexler, Wolfgang;Liu, Mengyang;Leitgeb, Rainer A.
通讯作者：
Leitgeb, Rainer A.