A micro-XRT image analysis and machine learning methodology for the characterisation of multi- particulate capsule formulations [Video Abstract]
Doerr, Frederik J.S. and Florence, Alastair J. (2020) A micro-XRT image analysis and machine learning methodology for the characterisation of multi- particulate capsule formulations [Video Abstract]. Elsevier, Amsterdam.
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Video (Doerr-Florence-IJPX-2020-image-analysis-and-machine-learning-methodology-for-the-characterisation-of-multi-particulate-capsule-video)
Doerr_Florence_IJPX_2020_image_analysis_and_machine_learning_methodology_for_the_characterisation_of_multi_particulate_capsule_video.mp4 Final Published Version License: ![]() Download (7MB) |
Official URL: https://doi.org/10.1016/j.ijpx.2020.100041
Abstract
Video abstract highlighting aspects of a micro-XRT image analysis and machine learning methodology for the characterisation of multi-particulate capsule formulations (https://doi.org/10.1016/j.ijpx.2020.100041).
Creators(s): |
Doerr, Frederik J.S. ![]() ![]() | Item type: | Other |
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ID code: | 71463 |
Notes: | 7MB; Online |
Keywords: | pharmaceutical formulation development, watershed image sementation, crystallisation, XRT particle structure analysis, machine learning, micro-XRT, Therapeutics. Pharmacology, Pharmaceutical Science |
Subjects: | Medicine > Therapeutics. Pharmacology |
Department: | Faculty of Science > Strathclyde Institute of Pharmacy and Biomedical Sciences Technology and Innovation Centre > Continuous Manufacturing and Crystallisation (CMAC) Strategic Research Themes > Advanced Manufacturing and Materials |
Depositing user: | Pure Administrator |
Date deposited: | 14 Feb 2020 00:03 |
Last modified: | 14 Jan 2021 03:14 |
Related URLs: | |
URI: | https://strathprints.strath.ac.uk/id/eprint/71463 |
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