| Literature DB >> 27656034 |
Guolan Lu1, Xulei Qin2, Dongsheng Wang3, Susan Muller4, Hongzheng Zhang4, Amy Chen4, Zhuo Georgia Chen3, Baowei Fei5.
Abstract
Hyperspectral imaging (HSI) is an emerging modality for medical applications and holds great potential for noninvasive early detection of cancer. It has been reported that early cancer detection can improve the survival and quality of life of head and neck cancer patients. In this paper, we explored the possibility of differentiating between premalignant lesions and healthy tongue tissue using hyperspectral imaging in a chemical induced oral cancer animal model. We proposed a novel classification algorithm for cancer detection using hyperspectral images. The method detected the dysplastic tissue with an average area under the curve (AUC) of 0.89. The hyperspectral imaging and classification technique may provide a new tool for oral cancer detection.Entities:
Keywords: 4NQO-induced oral cancer; Hyperspectral imaging; early cancer detection; image classification; random forest; superpixel
Year: 2016 PMID: 27656034 PMCID: PMC5028204 DOI: 10.1117/12.2216553
Source DB: PubMed Journal: Proc SPIE Int Soc Opt Eng ISSN: 0277-786X