Micro-Structural Analysis of Tablet Surface Layers by Intelligent Laser Speckle Classification (ILSC) Technique: an Application in the Study of both Surface Defects and Subsurface Granule Structures

Abstract

Purpose : As a consequence of the latest developments in laser technologies it is now possible to develop a low-cost and accurate tablet inspection system by the unification of optical and artificial intelligence methods. Method: The functionality of the proposed system is based on a sequence of texture analysis of laser speckle images (using laser sources of 650 nm and 808 nm : VIS/IR) followed by the optimization of texture parameters using Bayesian Networks (BN). Results: In the first part of this work, a Bayesian inference method was used to detect micro-scale tablet defects that are generated "progressively" during production whereas in the second part a Bayesian classifier method was used to discriminate between tablets made from different granule sizes. In part two, it was shown that (i) the comparatively higher energy (5mW) IR laser light generates different speckle effects than the lower energy visible (Red 3mW) by interacting with deeper sub-surface of the tablets and (ii) by using multiclassifier systems (MCS) to fuse the Bayesian classifiers from both types of speckle images it was possible to achieve a higher discrimination power (88% classification accuracy) for distinguishing between tablets made from different granule sizes than one can achieve from a single image type. Conclusion: It is suggested that this unified method has the potential to provide for a comprehensive analysis of both tablet quality attributes, on the one hand, and failure modes, on the other, that might be used in the development of a low cost tablet inspection system.

Progressive Observation of Covid-19 Vaccination Effects on Skin-Cellular Structures by Use of Intelligent Laser Speckle Classification (ILSC) Technique

“…(2) tested and used successfully in the last two decades with high accuracy [22,32]. The formulations are described by Eqs.…”

“…In the current literature, there is only one study [15] which unifies laser speckle contrast imaging with artificial intelligence (neural networks) but differs from our proposed work in terms of its application and outputs. Here, ILSC is an integrated technique [9,16,22] which is comprised of different disciplinary methods, providing high sensitivity and discrimination power to detect subtle differences even at the sub-cellular level. The method detects laser speckles' textural differences, not for only a single cell unit but rather on the whole cellular network, to detect any common property or structural changes in all cells simultaneously, since all cells are naturally identical to each other or react to external effects in the same way.…”

“…• Within this research, we have proven that the Covid-19 vaccine effect and possibly Covid-19 infection can be observed at a high frequency of data collection, with high reliability. "Multi-Classifier System" (MCS) is also applicable by the addition of more laser sources with different wavelengths (e.g., red, IR) [22][23][24]. • Speedy image acquisition and processing provide realtime skin analysis, thus enabling a continuous skin observation by successive data collection.…”

A review of emerging technologies enabling improved solid oral dosage form manufacturing and processing

“…The developed system was used to detect micro-sized surface defects produced following the tablet sticking. This system was also adopted for studying subsurface granule micro-structures [198].…”