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Deep convolutional neural networks: Outperforming established algorithms in the evaluation of industrial optical coherence tomography (OCT) images of pharmaceutical coatings
- Source :
- International Journal of Pharmaceutics: X, International Journal of Pharmaceutics: X, Vol 2, Iss, Pp 100058-(2020)
- Publication Year :
- 2020
- Publisher :
- Elsevier, 2020.
-
Abstract
- 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, monitoring film-coated tablets as well as single- and multi-layered pellets. CNN results were compared against results from established algorithms based on ellipse-fitting, as well as to human-annotated ground truth data. Performance benchmarks used include, efficiency (computation speed), sensitivity (number of detections from a defined test set) and accuracy (deviation from the reference method). The results were validated by comparing the output of several algorithms to data manually annotated by human experts and microscopy images of cross-sectional cuts of the same dosage forms as a reference method. In order to guarantee comparability for all results, the algorithms were executed on the same hardware. Since modern OCT systems must operate under real-time conditions in order to be implemented in-line into manufacturing lines, the necessary steps are discussed on how to achieve this goal without sacrificing the algorithmic performance and how to tailor a deep CNN to cope with the high amount of image noise and alterations in object appearance. The developed deep learning approach outperforms static algorithms currently available in pharma applications with respect to performance benchmarks, and represents the next level in real time evaluation of challenging industrial OCT image data.<br />Graphical abstract Unlabelled Image
- Subjects :
- Optical coherence tomography (OCT)
Ground truth
Image segmentation
medicine.diagnostic_test
Computer science
business.industry
Deep learning
lcsh:RS1-441
Pharmaceutical Science
Convolutional neural network
Convolutional neural networks (CNNs)
lcsh:Pharmacy and materia medica
Optical coherence tomography
Proof of concept
Single- and multi-layered coatings
Test set
medicine
Image noise
Artificial intelligence
business
Algorithm
Coating layer thickness
Research Paper
Subjects
Details
- Language :
- English
- ISSN :
- 25901567
- Volume :
- 2
- Database :
- OpenAIRE
- Journal :
- International Journal of Pharmaceutics: X
- Accession number :
- edsair.doi.dedup.....2c03ee35c4d900783e0ff6487d440763