Work

Segmentation of Drosophila heart in optical coherence microscopy images using convolutional neural networks

Year: 2018

Type: article

Abstract: 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 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.

Source: Journal of Biophotonics

DOI: 10.1002/jbio.201800146

Authors: Lian Duan, Xi Qin, Yuanhao He, Xialin Sang, Jinda Pan, Tao Xu, Jing Men, Rudolph E. Tanzi, Airong Li, Yutao Ma, Chao Zhou

Institutions: Lehigh University, Hainan University, Tianjin University, Wuhan University, State Key Laboratory of Software Engineering, Harvard University, Massachusetts General Hospital

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, Lehigh University, National Institutes of Health, National Eye Institute, National Institute of Biomedical Imaging and Bioengineering

Awards: High throughput optical coherence tomography (OCT)-based imaging platform for label-free, non-invasive characterization of 3D tumor spheroids., Novel optical imaging and pacing platform for developmental cardiology, G738160294, Integrated Optical Coherence Tomography and Microscopy for Molecular-Targeted Ima, G8293452648, Integrated Optical Coherence Tomography and Microscopy for Molecular-Targeted Ima, IDBR: Type A: Ultrahigh-Speed Space-Division Multiplexing Optical Coherence Tomography for Label-free and Non-destructive Biological Imaging, G9000077034, Space-division multiplexing optical coherence tomography for large-scale, millisecond resolution imaging of neural activity

OpenAlex ID: W2963876870

FWCI: 0.875

Cites: 41

Cited by: 16

Related to: 10