When specific staining is effective, different image processing and analysis algorithms can be developed that vary in their complexity, accuracy, and efficiency. In the field of medicine, when the SOIs cannot be highlighted by a specific staining (e.g., histochemical or immunohistochemical stainings), or when staining is not optimal or tissue is heterogeneous, then the techniques of stereology are the best alternative for estimating the parameter values of SOIs. In addition, while complex algorithms require careful validation of their results, stereology results require no validation since results are derived from a standard statistical analysis of grid elements and user-highlighted SOIs. If used properly, Stereology Analyzer is an effective alternative for image processing developers to validate a sequence of complex image processing algorithms. These computational results are then displayed on the computer’s screen and can be exported into third party environments (e.g., Excel, Word) for display and further analysis specific to the applicable field.Ĭounting methods: Points vs Boxes Image Processing Algorithm ValidationĮxperts in the applicable field can use Stereology Analyzer to quickly compute unbiased estimates of SOI parameters on virtual slides. The automatic computations are based on classical stereological and statistical analyses. The number of grid elements contained within the ROIs and the number of highlighted SOIs are then automatically counted and used to compute SOI parameters. Grid element alternatives include points, lines, frames, squares, and circles.Īfter the grid and ROIs are defined, the user manually highlights SOIs that are intersected by the grid elements. The types of grids are characterized by the geometric element that displays at the grid’s nodes. The type and spacing of the grid can be adjusted by the user to achieve the best estimates of the SOI parameters contained within the ROIs. Stereology Analyzer enables the user to optionally define one or more ROIs and a grid that overlays the ROIs or the whole image. Stereology Analyzer implements long-standing and accepted stereology techniques that employ an interactive grid overlaid on regions of interest (“ROI”) in a 2D image. Note that standard 2D image processing techniques will hardly provide 3D information from sections, except for the volume fraction value. By definition, stereology is the science that studies the geometric relationship between a structure that exists in 3D space and a set of images of the same structure that are fundamentally defined in 2D space (images of slices, sections, or projections). The term stereology was first introduced in 1961 when the International Society for Stereology (ISS) was founded by a small group of scientists, although the basis of stereology theory was defined more than 300 years ago. Stereology Analyzer graphical user interface Stereology Background MaterialsGrain, inclusion, boundary, pore, etc.MedicineTumor, vessels, cell, hotspot, etc.
STEREOLOGY CELL COUNTING SOFTWARE
Stereology Analyzer is a faithful implementation of long-accepted stereological and statistical methods in the context of today’s software technology. In fact, stereology is also frequently used to validate the proper performance of complex, automated algorithms. Where automated processes don’t exist or fail to compute SOI parameters reliably, stereology is the method of choice to estimate these parameters. The common factors in these fields are the need to characterize and quantify microscopic structures of interest (“SOI”) and the use of very large images (i.e., virtual slides or composite images). This tool is general in its implementation, but has applicability to various scientific domains, most commonly in medicine, materials science, and geology. Stereology Analyzer is a simple to use software tool for reliably estimating quantifications of important 3D structures. Stereological analysis of 3D structures using 2D section or projection images
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