Automatic detection of subviral particles in fluorescence microscopy images of Marburg virus infected cells using a convolutional neural network
Abstract: In collaboration with the Institute of Virology at the University of Marburg, a tracking algorithm has been developed in recent years. Thereby, for the tracking of subviral particles and their intracellular transport through the cell, the detection of these particles is the first major step. In this work a deep-learning based approach for automatic processing of fluorescence video sequences of virus infected cells is presented. The focus of this work was to generate synthetic data for training neuronal networks and to represent a particle using only a single delta peak. It was shown that a simple convolutional network is able to predict the particle positions with an almost identical accuracy as the algorithm developed by Kienzle, Rausch and colleagues [1-3], and that even a small dataset is sufficient for that purpose.
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
Automatic detection of subviral particles in fluorescence microscopy images of Marburg virus infected cells using a convolutional neural network ; volume:8 ; number:2 ; year:2022 ; pages:333-336 ; extent:4
Current directions in biomedical engineering ; 8, Heft 2 (2022), 333-336 (gesamt 4)
- Urheber
-
Naber, Sarah
Busch, Nils
Rausch, Andreas
Schanze, Thomas
- DOI
-
10.1515/cdbme-2022-1085
- URN
-
urn:nbn:de:101:1-2022090315310778784380
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:31 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Naber, Sarah
- Busch, Nils
- Rausch, Andreas
- Schanze, Thomas
Ähnliche Objekte (12)
FiloDetect: automatic detection of filopodia from fluorescence microscopy images
Fluorescence localization microscopy
Bridging fluorescence microscopy and electron microscopy
Automatic cell cycle analysis based on live cell fluorescence microscopy image sequences
Automatic imaging of Drosophila embryos with light sheet fluorescence microscopy on chip
Light sheet fluorescence microscopy
AxonDeepSeg: automatic axon and myelin segmentation from microscopy data using convolutional neural networks
Application of convolutional neural networks towards nuclei segmentation in localization-based super-resolution fluorescence microscopy images
Convolutional neural network transformer (CNNT) for fluorescence microscopy image denoising with improved generalization and fast adaptation
Expansion Microscopy combined with Super-Resolution Fluorescence Microscopy
Cryogenic super-resolved fluorescence microscopy
Ground state depletion fluorescence microscopy
FiloDetect: automatic detection of filopodia from fluorescence microscopy images
Fluorescence localization microscopy
Bridging fluorescence microscopy and electron microscopy
Automatic cell cycle analysis based on live cell fluorescence microscopy image sequences
Automatic imaging of Drosophila embryos with light sheet fluorescence microscopy on chip
Light sheet fluorescence microscopy
AxonDeepSeg: automatic axon and myelin segmentation from microscopy data using convolutional neural networks
Application of convolutional neural networks towards nuclei segmentation in localization-based super-resolution fluorescence microscopy images
Convolutional neural network transformer (CNNT) for fluorescence microscopy image denoising with improved generalization and fast adaptation
Expansion Microscopy combined with Super-Resolution Fluorescence Microscopy
Cryogenic super-resolved fluorescence microscopy
Ground state depletion fluorescence microscopy
FiloDetect: automatic detection of filopodia from fluorescence microscopy images
Fluorescence localization microscopy
Bridging fluorescence microscopy and electron microscopy
Automatic cell cycle analysis based on live cell fluorescence microscopy image sequences
Automatic imaging of Drosophila embryos with light sheet fluorescence microscopy on chip
Light sheet fluorescence microscopy
AxonDeepSeg: automatic axon and myelin segmentation from microscopy data using convolutional neural networks
Application of convolutional neural networks towards nuclei segmentation in localization-based super-resolution fluorescence microscopy images
Convolutional neural network transformer (CNNT) for fluorescence microscopy image denoising with improved generalization and fast adaptation
Expansion Microscopy combined with Super-Resolution Fluorescence Microscopy
Cryogenic super-resolved fluorescence microscopy