Abstract
ObjectivesAs computing technology and image analysis techniques have advanced, the practice of histology has grown from a purely qualitative method to one that is highly quantified. Current image analysis software is imprecise and prone to wide variation due to common artifacts and histological limitations. In order to minimize the impact of these artifacts, a more robust method for quantitative image analysis is required.Methods and ResultsHere we present a novel image analysis software, based on the hue saturation value color space, to be applied to a wide variety of histological stains and tissue types. By using hue, saturation, and value variables instead of the more common red, green, and blue variables, our software offers some distinct advantages over other commercially available programs. We tested the program by analyzing several common histological stains, performed on tissue sections that ranged from 4 µm to 10 µm in thickness, using both a red green blue color space and a hue saturation value color space.ConclusionWe demonstrated that our new software is a simple method for quantitative analysis of histological sections, which is highly robust to variations in section thickness, sectioning artifacts, and stain quality, eliminating sample-to-sample variation.
Highlights
For over a century, histological analysis of biological samples has led to greater understanding of biological mechanisms
Histological assessment is often used as a qualitative method by clinical pathologists and within research settings, localizing a specific biomarker in the tissue or exploring tissue morphology and remodeling
The well-known Golgi method elucidated the structure of the nervous system at the turn of the 20th century, and by combining advanced fluorescent stains with time-lapse photography, modern researchers can track the migration of individual sub-cellular structures such as mitochondria [1] or matrix vesicles [2]
Summary
Histological analysis of biological samples has led to greater understanding of biological mechanisms. Histological assessment is often used as a qualitative method by clinical pathologists and within research settings, localizing a specific biomarker in the tissue or exploring tissue morphology and remodeling. Qualitative histological analyses have contributed importantly to our knowledge of cellular and tissue anatomy. As methods of immunohistochemical staining have advanced, histological diagnoses and research have become more refined. The most common form of such analysis in histology requires that a researcher create a rubric for assigning a score to each experimental tissue sample. These scores may rely on a histologist’s experience and intuition and could be imprecise or subjective, and difficult to recreate exactly [4]
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