Bartschat, Andreas ; Allgeier, Stephan ; Scherr, Tim ; Stegmaier, Johannes ; Bohn, Sebastian ; Reichert, Klaus-Martin ; Kuijper, Arjan ; Reischl, Markus ; Stachs, Oliver ; Köhler, Bernd ; Mikut, Ralf (2019)
Fuzzy tissue detection for real-time focal control in corneal confocal microscopy.
In: at - Automatisierungstechnik, 67 (10)
doi: 10.1515/auto-2019-0034
Article
Abstract
Corneal confocal laser scanning microscopy is a promising method for in vivo investigation of cellular structures, e. g., of nerve fibers in the sub-basal nerve plexus. During recording, even slight displacements of the focal plane lead to images of adjacent tissue layers. In this work, we propose a closed-loop control of the focal plane. To detect and evaluate the visible tissues, we utilize the Bag of Visual Words approach to implement a customizable image processing pipeline for real-time applications. Furthermore, we show that the proposed model can be trained with small classification datasets and can be applied as a segmentation method. The proposed control loop, including tissue detection, is implemented in a proof-of-concept setup and shows promising results in a first evaluation with a human subject.
| Item Type: | Article | ||||
|---|---|---|---|---|---|
| Erschienen: | 2019 | ||||
| Creators: | Bartschat, Andreas ; Allgeier, Stephan ; Scherr, Tim ; Stegmaier, Johannes ; Bohn, Sebastian ; Reichert, Klaus-Martin ; Kuijper, Arjan ; Reischl, Markus ; Stachs, Oliver ; Köhler, Bernd ; Mikut, Ralf | ||||
| Type of entry: | Bibliographie | ||||
| Title: | Fuzzy tissue detection for real-time focal control in corneal confocal microscopy | ||||
| Language: | English | ||||
| Date: | 2019 | ||||
| Journal or Publication Title: | at - Automatisierungstechnik | ||||
| Volume of the journal: | 67 | ||||
| Issue Number: | 10 | ||||
| DOI: | 10.1515/auto-2019-0034 | ||||
| URL / URN: | https://doi.org/10.1515/auto-2019-0034 | ||||
| Abstract: | Corneal confocal laser scanning microscopy is a promising method for in vivo investigation of cellular structures, e. g., of nerve fibers in the sub-basal nerve plexus. During recording, even slight displacements of the focal plane lead to images of adjacent tissue layers. In this work, we propose a closed-loop control of the focal plane. To detect and evaluate the visible tissues, we utilize the Bag of Visual Words approach to implement a customizable image processing pipeline for real-time applications. Furthermore, we show that the proposed model can be trained with small classification datasets and can be applied as a segmentation method. The proposed control loop, including tissue detection, is implemented in a proof-of-concept setup and shows promising results in a first evaluation with a human subject. |
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| Uncontrolled Keywords: | Image classification Bag-of-words Laser scanning confocal microscopy Pattern recognition Tissue classifications Realtime feedback Tissue segmentation | ||||
| Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Mathematical and Applied Visual Computing |
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| Date Deposited: | 17 Apr 2020 09:59 | ||||
| Last Modified: | 17 Apr 2020 09:59 | ||||
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