Segmentation of Drosophila heart in optical coherence microscopy images using convolutional neural networks.
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ABSTRACT:
SUBMITTER: Duan L
PROVIDER: S-EPMC6289629 | biostudies-literature | 2018 Dec
REPOSITORIES: biostudies-literature
Publications
Segmentation of Drosophila heart in optical coherence microscopy images using convolutional neural networks.
Duan Lian L Qin Xi X He Yuanhao Y Sang Xialin X Pan Jinda J Xu Tao T Men Jing J Tanzi Rudolph E RE Li Airong A Ma Yutao Y Zhou Chao C
Journal of biophotonics 20180806 12
Convolutional neural networks (CNNs) 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 CNN model, the heart regions through multiple heartbeat cycles can be marked with an intersection over union of ~86%. Various morphological and dynamical cardiac parameters c ...[more]
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