@inproceedings{100bcc8935964f11946828ce4bfbe186,
title = "Quantitative wavelength analysis and image classification for intraoperative cancer diagnosis with hyperspectral imaging",
abstract = "Complete surgical removal of tumor tissue is essential for postoperative prognosis after surgery. Intraoperative tumor imaging and visualization are an important step in aiding surgeons to evaluate and resect tumor tissue in real time, thus enabling more complete resection of diseased tissue and better conservation of healthy tissue. As an emerging modality, hyperspectral imaging (HSI) holds great potential for comprehensive and objective intraoperative cancer assessment. In this paper, we explored the possibility of intraoperative tumor detection and visualization during surgery using HSI in the wavelength range of 450 nm - 900 nm in an animal experiment. We proposed a new algorithm for glare removal and cancer detection on surgical hyperspectral images, and detected the tumor margins in five mice with an average sensitivity and specificity of 94.4% and 98.3%, respectively. The hyperspectral imaging and quantification method have the potential to provide an innovative tool for image-guided surgery.",
keywords = "Active contour, Glare removal, Hyperspectral imaging, Intraoperative tumor detection, Mutual information, Support vector machine, Wavelength optimization",
author = "Guolan Lu and Xulei Qin and Dongsheng Wang and Chen, {Zhuo Georgia} and Baowei Fei",
note = "Publisher Copyright: {\textcopyright} 2015 SPIE.; Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling ; Conference date: 22-02-2015 Through 24-02-2015",
year = "2015",
doi = "10.1117/12.2082284",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Webster, {Robert J.} and Yaniv, {Ziv R.}",
booktitle = "Medical Imaging 2015",
}