MATEC Web Conf.
Volume 154, 2018The 2nd International Conference on Engineering and Technology for Sustainable Development (ICET4SD 2017)
|Number of page(s)||5|
|Published online||28 February 2018|
Color feature extraction of HER2 Score 2+ overexpression on breast cancer using Image Processing
Master of Informatics Engineering Universitas Islam Indonesia, Indonesia
2 Master of Informatics Engineering Universitas Islam Indonesia, Indonesia
3 Faculty of Medicine Universitas Muhammadiyah Yogyakarta, Indonesia
* Corresponding author: email@example.com
One of the major challenges in the development of early diagnosis to assess HER2 status is recognized in the form of Gold Standard. The accuracy, validity and refraction of the Gold Standard HER2 methods are widely used in laboratory (Perez, et al., 2014). Method determining the status of HER2 (human epidermal growth factor receptor 2) is affected by reproductive problems and not reliable in predicting the benefit from anti-HER2 therapy (Nuciforo, et al., 2016). We extracted color features by methods adopting Statistics-based segmentation using a continuous-scale naïve Bayes approach. In this study, there were three parts of the main groups, namely image acquisition, image segmentation, and image testing. The stages of image acquisition consisted of image data collection and color deconvolution. The stages of image segmentation consisted of color features, classifier training, classifier prediction, and skeletonization. The stages of image testing were image testing, expert validation, and expert validation results. Area segmentation of the membrane is false positive and false negative. False positive and false negative from area are called the area of system failure. The failure of the system can be validated by experts that the results of segmentation region is not membrane HER2 (noise) and the segmentation of the cytoplasm region. The average from 40 data of HER2 score 2+ membrane images show that 75.13% of the area is successfully recognized by the system.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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