Publication

Quantitative Image Analysis for Evaluating the Coating Thickness and Pore Distribution in Coated Small Particles

Laksmana, F. L., Van Vliet, L. J., Hartman Kok, P. J. A., Vromans, H., Frijlink, H. W. & Van der Voort Maarschalk, K., Apr-2009, In : Pharmaceutical Research. 26, 4, p. 965-976 12 p.

Research output: Contribution to journalArticleAcademicpeer-review

APA

Laksmana, F. L., Van Vliet, L. J., Hartman Kok, P. J. A., Vromans, H., Frijlink, H. W., & Van der Voort Maarschalk, K. (2009). Quantitative Image Analysis for Evaluating the Coating Thickness and Pore Distribution in Coated Small Particles. Pharmaceutical Research, 26(4), 965-976. https://doi.org/10.1007/s11095-008-9805-y

Author

Laksmana, F L ; Van Vliet, L J ; Hartman Kok, P J A ; Vromans, H ; Frijlink, H W ; Van der Voort Maarschalk, K. / Quantitative Image Analysis for Evaluating the Coating Thickness and Pore Distribution in Coated Small Particles. In: Pharmaceutical Research. 2009 ; Vol. 26, No. 4. pp. 965-976.

Harvard

Laksmana, FL, Van Vliet, LJ, Hartman Kok, PJA, Vromans, H, Frijlink, HW & Van der Voort Maarschalk, K 2009, 'Quantitative Image Analysis for Evaluating the Coating Thickness and Pore Distribution in Coated Small Particles', Pharmaceutical Research, vol. 26, no. 4, pp. 965-976. https://doi.org/10.1007/s11095-008-9805-y

Standard

Quantitative Image Analysis for Evaluating the Coating Thickness and Pore Distribution in Coated Small Particles. / Laksmana, F L; Van Vliet, L J; Hartman Kok, P J A; Vromans, H; Frijlink, H W; Van der Voort Maarschalk, K.

In: Pharmaceutical Research, Vol. 26, No. 4, 04.2009, p. 965-976.

Research output: Contribution to journalArticleAcademicpeer-review

Vancouver

Laksmana FL, Van Vliet LJ, Hartman Kok PJA, Vromans H, Frijlink HW, Van der Voort Maarschalk K. Quantitative Image Analysis for Evaluating the Coating Thickness and Pore Distribution in Coated Small Particles. Pharmaceutical Research. 2009 Apr;26(4):965-976. https://doi.org/10.1007/s11095-008-9805-y


BibTeX

@article{5c0be5da4b5c4c1ab65266c1a36cf251,
title = "Quantitative Image Analysis for Evaluating the Coating Thickness and Pore Distribution in Coated Small Particles",
abstract = "This study aims to develop a characterization method for coating structure based on image analysis, which is particularly promising for the rational design of coated particles in the pharmaceutical industry.The method applies the MATLAB image processing toolbox to images of coated particles taken with Confocal Laser Scanning Microscopy (CSLM). The coating thicknesses have been determined along the particle perimeter, from which a statistical analysis could be performed to obtain relevant thickness properties, e.g. the minimum coating thickness and the span of the thickness distribution. The characterization of the pore structure involved a proper segmentation of pores from the coating and a granulometry operation.The presented method facilitates the quantification of porosity, thickness and pore size distribution of a coating. These parameters are considered the important coating properties, which are critical to coating functionality. Additionally, the effect of the coating process variations on coating quality can straight-forwardly be assessed.Enabling a good characterization of the coating qualities, the presented method can be used as a fast and effective tool to predict coating functionality. This approach also enables the influence of different process conditions on coating properties to be effectively monitored, which latterly leads to process tailoring.",
keywords = "Algorithms, Cellulose, Dosage Forms, Image Processing, Computer-Assisted, Methylcellulose, Microscopy, Confocal, Models, Statistical, Particle Size, Porosity, Technology, Pharmaceutical, Time Factors",
author = "Laksmana, {F L} and {Van Vliet}, {L J} and {Hartman Kok}, {P J A} and H Vromans and Frijlink, {H W} and {Van der Voort Maarschalk}, K",
year = "2009",
month = "4",
doi = "10.1007/s11095-008-9805-y",
language = "English",
volume = "26",
pages = "965--976",
journal = "Pharmaceutical Research",
issn = "0724-8741",
publisher = "SPRINGER/PLENUM PUBLISHERS",
number = "4",

}

RIS

TY - JOUR

T1 - Quantitative Image Analysis for Evaluating the Coating Thickness and Pore Distribution in Coated Small Particles

AU - Laksmana, F L

AU - Van Vliet, L J

AU - Hartman Kok, P J A

AU - Vromans, H

AU - Frijlink, H W

AU - Van der Voort Maarschalk, K

PY - 2009/4

Y1 - 2009/4

N2 - This study aims to develop a characterization method for coating structure based on image analysis, which is particularly promising for the rational design of coated particles in the pharmaceutical industry.The method applies the MATLAB image processing toolbox to images of coated particles taken with Confocal Laser Scanning Microscopy (CSLM). The coating thicknesses have been determined along the particle perimeter, from which a statistical analysis could be performed to obtain relevant thickness properties, e.g. the minimum coating thickness and the span of the thickness distribution. The characterization of the pore structure involved a proper segmentation of pores from the coating and a granulometry operation.The presented method facilitates the quantification of porosity, thickness and pore size distribution of a coating. These parameters are considered the important coating properties, which are critical to coating functionality. Additionally, the effect of the coating process variations on coating quality can straight-forwardly be assessed.Enabling a good characterization of the coating qualities, the presented method can be used as a fast and effective tool to predict coating functionality. This approach also enables the influence of different process conditions on coating properties to be effectively monitored, which latterly leads to process tailoring.

AB - This study aims to develop a characterization method for coating structure based on image analysis, which is particularly promising for the rational design of coated particles in the pharmaceutical industry.The method applies the MATLAB image processing toolbox to images of coated particles taken with Confocal Laser Scanning Microscopy (CSLM). The coating thicknesses have been determined along the particle perimeter, from which a statistical analysis could be performed to obtain relevant thickness properties, e.g. the minimum coating thickness and the span of the thickness distribution. The characterization of the pore structure involved a proper segmentation of pores from the coating and a granulometry operation.The presented method facilitates the quantification of porosity, thickness and pore size distribution of a coating. These parameters are considered the important coating properties, which are critical to coating functionality. Additionally, the effect of the coating process variations on coating quality can straight-forwardly be assessed.Enabling a good characterization of the coating qualities, the presented method can be used as a fast and effective tool to predict coating functionality. This approach also enables the influence of different process conditions on coating properties to be effectively monitored, which latterly leads to process tailoring.

KW - Algorithms

KW - Cellulose

KW - Dosage Forms

KW - Image Processing, Computer-Assisted

KW - Methylcellulose

KW - Microscopy, Confocal

KW - Models, Statistical

KW - Particle Size

KW - Porosity

KW - Technology, Pharmaceutical

KW - Time Factors

U2 - 10.1007/s11095-008-9805-y

DO - 10.1007/s11095-008-9805-y

M3 - Article

VL - 26

SP - 965

EP - 976

JO - Pharmaceutical Research

JF - Pharmaceutical Research

SN - 0724-8741

IS - 4

ER -

ID: 4856809