Open AccessIdentification of cancerous gastric cells based on common features extracted from hyperspectral microscopic images
Author(s) -
Siqi Zhu,
Kang Su,
Yumeng Liu,
Hao Yin,
Zhen Li,
Furong Huang,
Zhenqiang Chen,
Weidong Chen,
Ge Zhang,
Yihong Chen
Publication year - 2015
Publication title -
biomedical optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.6.001135
Subject(s) - hyperspectral imaging , h&e stain , stain , spectral imaging , cancer , transmission (telecommunications) , artificial intelligence , pattern recognition (psychology) , pathology , computer science , staining , biology , medicine , optics , physics , genetics , telecommunications
We construct a microscopic hyperspectral imaging system to distinguish between normal and cancerous gastric cells. We study common transmission-spectra features that only emerge when the samples are dyed with hematoxylin and eosin (H&E) stain. Subsequently, we classify the obtained visible-range transmission spectra of the samples into three zones. Distinct features are observed in the spectral responses between the normal and cancerous cell nuclei in each zone, which depend on the pH level of the cell nucleus. Cancerous gastric cells are precisely identified according to these features. The average cancer-cell identification accuracy obtained with a backpropagation algorithm program trained with these features is 95%.