Automated image analysis systems that provide detailed morphological information are rapidly replacing manual microscopy as the most effective method of characterizing both particle shape and size. These sophisticated new instruments use the latest technology to provide useful and actionable insight. Here are 8 reasons you should consider upgrading:
Automated imaging systems measure both particle size and shape in a single measurement over a size range from less than a micron to over a millimeter. This provides a much deeper understanding of the entire sample and can enable differentiation of samples that can’t easily be discriminated by size alone. By combining measurements such as particle length and width with 2D shape assessments such as circularity, convexity and elongation, a more accurate picture of each individual particle is produced, giving a more complete understanding of a sample’s characteristics.
Automated imaging systems provide substantial time savings when compared with manual microscopy, due to the streamlining of various operations as well as the convenience of in-built data analysis. Indeed, automated image analysis can measure tens of thousands of particles in just a few minutes – less time than manual microscopy would take to measure just a handful. This enables operators to generate statistically significant data on a host of particle size and shape parameters much more quickly and easily.
Sophisticated automated imaging systems can analyze both wet and dry samples, providing flexibility when measuring a wide array of sample types including dry powders, suspensions and filters. Appropriate sample preparation prior to analysis is key to accurate, consistent and reliable measurements, which rely on good spatial separation and representative sampling of particles. This is ensured by the provision of dedicated sample preparation accessories, including dry powder dispersion units, filter holders and various wet dispersion cells.
Accuracy and reliability are key attributes of automated image analysis systems and are highly dependent on the quality and resolution of particle images. Automated imaging systems, such as the Morphologi 4 range , produce high quality greyscale images of every particle measured. The high-quality intensity information from the greyscale image enables accurate determination of particle size and shape and a clearer insight into the relative thickness or density of particles, and their surface homogeneity.
An automated image analysis system delivers non-subjective, robust and reproducible particle measurements for improved data confidence. Intelligent algorithms, such as Sharp Edge, automatically separate particle images from background making method development easier. Standard operating procedures (SOPs) define all the software and hardware variables from sample dispersion to result reporting and SOP-driven operation ensure that critical processes of the analysis, such as the focusing and illumination, as well as the particle segmentation are operator independent.
The integration of Raman spectroscopy with automated imaging eliminates the need for two separate analysis techniques, saving valuable time and limiting the complexities associated with interpreting and correlating different data sets. Morphologically-Directed Raman Spectroscopy (MDRS) provides an additional capability over imaging alone, by allowing the physical and chemical characteristics of individual components to be analyzed. Individual chemical classes from within a complex mixture can be identified, delivering valuable insight into the structure and composition of a material, such as a pharmaceutical formulation or a cement blend.
Automated image analysis is easier to use than manual microscopy because, as the name suggests, many of the processes are automated. A sample is loaded into the system and once the start button is pressed, the Standard Operating Procedure (SOP) is activated. The imaging instrument automatically disperses the dry sample and analyzes it without the need for any further operator interaction. The particle images are automatically captured, measured, analyzed and classified, with over 20 morphological parameters being measured.
With the ability to analyze hundreds of thousands of particles per measurement, statistically meaningful results can be obtained rapidly, and analyzed in a way that allows clear trends and relationships to be identified. Rapid comparison of such large numbers of morphological parameter data sets is achieved using an integrated data comparison tool that automatically groups similar records together based on a chosen parameter or set of criteria. Particle images can be easily classified according to any combination of particle size and shape parameters, and if available, their chemical composition.
