Image analysis of breast cancer immunohistochemistry-stained sections using ImageJ: an RGB-based model (Journal article)

Vrekoussis, T./ Chaniotis, V./ Navrozoglou, I./ Dousias, V./ Pavlakis, K./ Stathopoulos, E. N./ Zoras, O.

BACKGROUND: Image analysis of tissue sections using RGB image profiling is a modern accepted technique. MATERIALS AND METHODS: A new method of RGB analysis, using the freeware ImageJ, is presented which can be applied to sections with either nuclear or cytoplasmic staining. The step-by-step process is presented and the method is tested using breast cancer specimens immunostained for CK-19 and estrogen receptors. RESULTS: This image analysis easily discriminates CK-19 and estrogen receptor positivity in prepared breast cancer specimens. The method is easy to perform, without the need for previous image transformations. CONCLUSION: Compared to previous methods, this method proved more accurate in estimating the actual colours that an observer recognizes as positive after immunostaining. Further studies are needed to evaluate whether this method is efficient enough to be applied in clinical practice.
Institution and School/Department of submitter: Πανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Υγείας. Τμήμα Ιατρικής
Keywords: Algorithms,Automation,Breast Neoplasms/*metabolism/*pathology,Diagnostic Imaging/*methods,Female,Humans,*Image Processing, Computer-Assisted,Immunoenzyme Techniques,Keratin-19/*metabolism,*Models, Molecular,Receptors, Estrogen/*metabolism,Software
ISSN: 1791-7530
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά)

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