Akbari et al.39 used a hyperspectral VIS-NIR-SWIR imaging system for detection and monitoring of intestinal ischemia in vivo in a porcine model. The instrumentation included two halogen lamps for illumination and two cameras (a 400- to 1000-nm camera and a 900- to 1700-nm camera) for image detection. The SWIR (900 to 1700 nm) camera provided a spectral resolution of 5 nm by use of a 30-m slit. The slit provided one thin “slice” of the image at a time, so the slit was scanned across the object using a “push-broom” method to obtain the entire wide-field image. Images were obtained for 157 wavelength bands in the 900- to 1700-nm range; each image took to acquire and the spatial resolution of the images was . In the ischemia experiment, a clamping procedure was performed on a portion of the intestine and the associated blood vessels. Wide-field reflectance images of the exposed abdominal cavity, with peritoneum, spleen, intestine, and bladder within the field of view, were acquired intraoperatively before clamping and , , and after clamping. The reflectance data were analyzed with a quantitative, feature-based method, in order to locate spectral regions in which the lineshape measured from ischemic tissue was the most notably different than that measured from normal tissue. To accomplish this, the derivative of the reflectance spectrum was evaluated at each wavelength, and the absolute value of the sum of these derivatives was calculated for different subsets of the measured wavelength range. It was found that the range from 999 to 1182 nm was optimal for distinguishing ischemic spectra from normal spectra, so the magnitude of the sum of the derivatives in this region was defined to be the ischemia index. Camera pixels with ischemia index values that surpassed a specific threshold were labeled as ischemic. Using the SWIR images, the regions of ischemia were classified with a false positive rate of 8% and a false negative rate of 7%. Akbari et al.40 also performed a similar study on freshly excised human gastric tumors, using the same technology as in 39. With a mathematical approach similar to that employed in 39, a “cancer index” was calculated by summing the square of the reflectance derivative from 1226 to 1251 nm and the square of the reflectance derivative from 1288 to 1370 nm. Despite being based purely on mathematical differences in spectral lineshape instead of biophysical tissue optics parameters, the model distinguished cancerous tissues from noncancerous tissues with a false positive rate of 7% and a false negative rate of 9%. Furthermore, the method showed potential for detecting tumors buried beneath up to to 3 mm of benign mucosal tissue.