A New Automated Histomorphometric MATLAB Algorithm for Immunohistochemistry Analysis Using Whole Slide Imaging.

The use of animal models along with the employment of advanced and sophisticated stereological methods for assessing bone quality combined with the use of statistical methods to evaluate the effectiveness of bone therapies has made it possible to investigate the pathways that regulate bone responses to medical devices. Image analysis of histomorphometric measurements remains a time-consuming task, as the image analysis software currently available does not allow for automated image segmentation. Such a feature is usually obtained by machine learning and with software platforms that provide image-processing tools such as MATLAB.

Histomorphometric Evaluation of Critical-Sized Bone Defects Using Osteomeasure and Aperio Image Analysis Systems.

Most histological evaluations of critical-sized bone defects are limited to the analysis of a few regions of interest at a time. Manual and semiautomated histomorphometric approaches often have intra- and interobserver subjectivity, as well as variability in image analysis methods. Moreover, the production of large image data sets makes histological assessment and histomorphometric analysis labor intensive and time consuming.