Quantitative image analysis is a form of imaging that includes microscopic histological quantification, video microscopy, image analysis, and image processing. Hallmarks are the generation of reliable, reproducible, and efficient measurements via strict calibration and step-by-step control of the acquisition, storage and evaluation of images with dedicated hardware and software.
Major advantages of quantitative image analysis over traditional techniques include sophisticated calibration systems, interaction, speed, and control of inter- and intraobserver variation. This results in a well controlled environment, which is essential for quality control and reproducibility, and helps to optimize sensitivity and specificity. To achieve this, an optimal quantitative image analysis system combines solid software engineering with easy interactivity with the operator. Moreover, the system also needs to be as transparent as possible in generating the data because a “black box design” will deliver uncontrollable results.
In addition to these more general aspects, specifically for the analysis of synovial tissue the necessity of interactivity is highlighted by the added value of identification and quantification of information as present in areas such as the intimal lining layer, blood vessels, and lymphocyte aggregates.
Speed is another important aspect of digital cytometry. Currently, rapidly increasing numbers of samples, together with accumulation of a variety of markers and detection techniques has made the use of traditional analysis techniques such as manual quantification and semi-quantitative analysis unpractical. It can be anticipated that the development of even more powerful computer systems with sophisticated software will further facilitate reliable analysis at high speed.