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Unsupervised real-time evaluation of optical coherence tomography (OCT) images of solid oral dosage forms

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Abstract

Automatic segmentation of images, which is now feasible through an increase in available computing power, has become an important challenge in many fields. A key technology for obtaining such images is optical coherence tomography (OCT), which is already widely applied in ophthalmology and more recently in the pharmaceutical industry, as a method for real-time monitoring of solid oral dosage form coating processes. Accurately detecting the boundaries of objects in OCT images is required for a meaningful automatic evaluation. During in-line monitoring, the evaluation time for each image is a crucial factor to enable the real-time analysis of large amounts of data. The segmentation of images has previously been achieved via machine learning methods, which generally require a large number of training examples. This work aims to overcome this limitation by employing unsupervised machine learning for the segmentation of OCT images of coated pharmaceutical tablets. An adapted clustering method was specifically developed to achieve the fast real-time detection of the coating layer’s boundaries in OCT-generated images. A newly developed parallel implementation of DBSCAN, that is well suited for image evaluation, makes it possible to use this novel method for real-time process analytical technology (PAT) applications. This approach has been shown to be significantly faster than so far established methods for segmenting similar OCT images. Furthermore, the image-specific parallelized DBSCAN algorithm has been shown to be around three times faster than other parallel implementations.

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Acknowledgements

The COMET Center Research Center Pharmaceutical Engineering (RCPE) is funded within the framework of COMET—Competence Centers for Excellent Technologies by BMK, BMDW, Land Steiermark and SFG. The COMET program is managed by the FFG.

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Authors and Affiliations

  1. Research Center Pharmaceutical Engineering GmbH, Inffeldgasse 13, 8010, Graz, Austria

    Elisabeth Fink, Phillip Clarke, Martin Spoerk & Johannes Khinast

  2. Institute of Process and Particle Engineering, Technical University Graz, Inffeldgasse 13, 8010, Graz, Austria

    Johannes Khinast

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  1. Elisabeth Fink
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  2. Phillip Clarke
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  4. Johannes Khinast
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Correspondence to Elisabeth Fink.

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Fink, E., Clarke, P., Spoerk, M. et al. Unsupervised real-time evaluation of optical coherence tomography (OCT) images of solid oral dosage forms. J Real-Time Image Proc 19, 881–892 (2022). https://doi.org/10.1007/s11554-022-01229-9

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