Research Papers: Imaging

Spectral-spatial classification for noninvasive cancer detection using hyperspectral imaging

[+] Author Affiliations
Guolan Lu

Georgia Institute of Technology and Emory University, The Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia 30329, United States

Luma Halig, Xulei Qin

Emory University School of Medicine, Department of Radiology and Imaging Sciences, Atlanta, Georgia 30329, United States

Dongsheng Wang, Zhuo Georgia Chen

Emory University School of Medicine, Department of Hematology and Medical Oncology, Atlanta, Georgia 30329, United States

Baowei Fei

Georgia Institute of Technology and Emory University, The Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia 30329, United States

Emory University School of Medicine, Department of Radiology and Imaging Sciences, Atlanta, Georgia 30329, United States

Emory University, Department of Mathematics & Computer Science, Atlanta, Georgia 30329, United States

Winship Cancer Institute of Emory University, Atlanta, Georgia 30329, United States

J. Biomed. Opt. 19(10), 106004 (Oct 02, 2014). doi:10.1117/1.JBO.19.10.106004
History: Received July 4, 2014; Revised August 21, 2014; Accepted September 10, 2014
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Abstract.  Early detection of malignant lesions could improve both survival and quality of life of cancer patients. Hyperspectral imaging (HSI) has emerged as a powerful tool for noninvasive cancer detection and diagnosis, with the advantage of avoiding tissue biopsy and providing diagnostic signatures without the need of a contrast agent in real time. We developed a spectral-spatial classification method to distinguish cancer from normal tissue on hyperspectral images. We acquire hyperspectral reflectance images from 450 to 900 nm with a 2-nm increment from tumor-bearing mice. In our animal experiments, the HSI and classification method achieved a sensitivity of 93.7% and a specificity of 91.3%. The preliminary study demonstrated that HSI has the potential to be applied in vivo for noninvasive detection of tumors.

© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Guolan Lu ; Luma Halig ; Dongsheng Wang ; Xulei Qin ; Zhuo Georgia Chen, et al.
"Spectral-spatial classification for noninvasive cancer detection using hyperspectral imaging", J. Biomed. Opt. 19(10), 106004 (Oct 02, 2014). ; http://dx.doi.org/10.1117/1.JBO.19.10.106004


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