Literature DB >> 18003125

Colour-texture based image analysis method for assessing the hormone receptors status in breast tissue sections.

Spiros Kostopoulos1, Dionisis Cavouras, Antonis Daskalakis, Panagiotis Bougioukos, Pantelis Georgiadis, George C Kagadis, Ioannis Kalatzis, Panagiota Ravazoula, George Nikiforidis.   

Abstract

Hormone receptors have been used in prognosis of breast carcinomas and their positive status is of clinical value in hormonal therapy. Determination of this status is based on the subjective visual inspection of the stained nuclei in the specimens. The aim of this study was the assessment of the estrogen receptor's (ER) positive status of breast carcinomas, by means of colour-texture based image analysis methodology. Twenty two cases of immunohistochemically (IHC) stained breast biopsies were initially assessed by a histopathologist for ER positive status, following a clinical scoring protocol. Custom-designed image analysis software was developed for automatically assessing the ER positive status, employing colour textural features and the k-Nearest Neighbor weighted votes classification algorithm. Computer-based image analysis system resulted in 86.4% overall accuracy and in 0.875 Kendall's coefficient of concordance (p<0.001), ranking correctly 19/22 cases. Colour-texture analysis of IHC stained specimens might have an impact in the quantitative assessment of ER status.

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Year:  2007        PMID: 18003125     DOI: 10.1109/IEMBS.2007.4353459

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  3 in total

1.  Automation of immunohistochemical evaluation in breast cancer using image analysis.

Authors:  Keerthana Prasad; Avani Tiwari; Sandhya Ilanthodi; Gopalakrishna Prabhu; Muktha Pai
Journal:  World J Clin Oncol       Date:  2011-04-10

2.  ImmunoRatio: a publicly available web application for quantitative image analysis of estrogen receptor (ER), progesterone receptor (PR), and Ki-67.

Authors:  Vilppu J Tuominen; Sanna Ruotoistenmäki; Arttu Viitanen; Mervi Jumppanen; Jorma Isola
Journal:  Breast Cancer Res       Date:  2010-07-27       Impact factor: 6.466

3.  Breast cancer characterization based on image classification of tissue sections visualized under low magnification.

Authors:  C Loukas; S Kostopoulos; A Tanoglidi; D Glotsos; C Sfikas; D Cavouras
Journal:  Comput Math Methods Med       Date:  2013-08-31       Impact factor: 2.238

  3 in total

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