A CNN Framework Based on Line Annotations for Detecting Nematodes in Microscopic Images
Chen L, Strauch M, Daub M, Jiang X, Jansen M, Luigs HG, Schultz-Kuhlmann S, Krussel S, Merhof D (2020)
Publication Type: Conference contribution
Publication year: 2020
Journal
Publisher: IEEE Computer Society
Book Volume: 2020-April
Pages Range: 508-512
Conference Proceedings Title: Proceedings - International Symposium on Biomedical Imaging
Event location: Iowa City, IA, USA
ISBN: 9781538693308
DOI: 10.1109/ISBI45749.2020.9098465
Abstract
Plant parasitic nematodes cause damage to crop plants on a global scale. Robust detection on image data is a prerequisite for monitoring such nematodes, as well as for many biological studies involving the nematode C. elegans, a common model organism. Here, we propose a framework for detecting worm-shaped objects in microscopic images that is based on convolutional neural networks (CNNs). We annotate nematodes with curved lines along the body, which is more suitable for worm-shaped objects than bounding boxes. The trained model predicts worm skeletons and body endpoints. The endpoints serve to untangle the skeletons from which segmentation masks are reconstructed by estimating the body width at each location along the skeleton. With light-weight backbone networks, we achieve 75.85% precision, 73.02% recall on a potato cyst nematode data set and 84.20% precision, 85.63% recall on a public C. elegans data set.
Involved external institutions
LemnaTec GmbH
Germany (DE)
Landwirtschaftskammer Niedersachsen (LWK) / Chamber of Agriculture in Lower Saxony
Germany (DE)
Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen
Germany (DE)
Julius Kühn-Institut – Bundesforschungsinstitut für Kulturpflanzen (JKI)
Germany (DE)
Germany (DE)
Landwirtschaftskammer Niedersachsen (LWK) / Chamber of Agriculture in Lower Saxony
Germany (DE)
Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen
Germany (DE)
Julius Kühn-Institut – Bundesforschungsinstitut für Kulturpflanzen (JKI)
Germany (DE)
How to cite
APA:
Chen, L., Strauch, M., Daub, M., Jiang, X., Jansen, M., Luigs, H.G.,... Merhof, D. (2020). A CNN Framework Based on Line Annotations for Detecting Nematodes in Microscopic Images. In Proceedings - International Symposium on Biomedical Imaging (pp. 508-512). Iowa City, IA, USA: IEEE Computer Society.
MLA:
Chen, Long, et al. "A CNN Framework Based on Line Annotations for Detecting Nematodes in Microscopic Images." Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, ISBI 2020, Iowa City, IA, USA IEEE Computer Society, 2020. 508-512.
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