Deep convolutional neural networks: Outperforming established algorithms in the evaluation of industrial optical coherence tomography (OCT) images of pharmaceutical coatings
This paper presents a novel evaluation approach for optical coherence tomography (OCT) image analysis of pharmaceutical solid dosage forms based on deep convolutional neural networks (CNNs). As a proof of concept, CNNs were applied to image data from both, in- and at-line OCT implementations, monito...
Main Authors: | Matthias Wolfgang, Michael Weißensteiner, Phillip Clarke, Wen-Kai Hsiao, Johannes G. Khinast |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2020-12-01
|
Series: | International Journal of Pharmaceutics: X |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2590156720300207 |
Similar Items
-
A Review of the Applications of OCT for Analysing Pharmaceutical Film Coatings
by: Hungyen Lin, et al.
Published: (2018-12-01) -
Feasibility of In-line monitoring of critical coating quality attributes via OCT: Thickness, variability, film homogeneity and roughness
by: Stephan Sacher, et al.
Published: (2021-12-01) -
Spectral Domain Optical Coherence Tomography for Non-Destructive Testing of Protection Coatings on Metal Substrates
by: Marcel Lenz, et al.
Published: (2017-04-01) -
Comparison of retinal nerve fiber layer and macular thickness measurements with Stratus OCT and OPKO/OTI OCT devices in healthy subjects
by: Ahmet Ozkok, et al.
Published: (2015-02-01) -
Optical coherence tomography detection of retinal neural loss in patients with tuberous sclerosis
by: Paula Basso Dias, et al.
Published: (2024-02-01)