title: A novel quantitative approach for eliminating sample-to-sample variation using a hue saturation value analysis program.
abstract: OBJECTIVE
  As 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.
  
  
  RESULTS
  Here 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.
  
  
  CONCLUSIONS
  We 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.
authors.affiliation: Center for Interdisciplinary Cardiovascular Sciences, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
authors.forename: Katsumi
authors.initials: K
authors.lastname: Yabusaki
authors.affiliation: Center for Interdisciplinary Cardiovascular Sciences, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
authors.forename: Tyler
authors.initials: T
authors.lastname: Faits
authors.affiliation: Center for Interdisciplinary Cardiovascular Sciences, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
authors.forename: Eri
authors.initials: E
authors.lastname: McMullen
authors.affiliation: Center for Interdisciplinary Cardiovascular Sciences, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
authors.forename: Jose Luiz
authors.initials: JL
authors.lastname: Figueiredo
authors.affiliation: Center for Interdisciplinary Cardiovascular Sciences, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America; Center for Excellence in Vascular Biology, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
authors.forename: Masanori
authors.initials: M
authors.lastname: Aikawa
authors.affiliation: Center for Interdisciplinary Cardiovascular Sciences, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America; Center for Excellence in Vascular Biology, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
authors.forename: Elena
authors.initials: E
authors.lastname: Aikawa
mesh_terms: D003116:Color; D006653:Histology / Q000592:standards*; D007091:Image Processing, Computer-Assisted; D015203:Reproducibility of Results; D012984:Software