Label-free HSI for Surgical Margin Assessment
Quantification Tools for HSI During Surgical Guidance
Spectral-Spatial Classification Methods for Tumor Detection
Minimum Spanning Forest Based Method for HSI
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 nm to 900 nm with a 2-nm increment from tumor-bearing mice. In our animal experiments, the hyperspectral imaging 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.
Effects of Pre-processing on Spectra