Summary, discussion and future perspectives of the incident light and the optical properties of the tissue. The reflectance spectrum is used to characterize the nature or type of the tissue being studied. Human color vision is trichromatic: the eye has three cone types for blue, green and red light. Hyperspectral imaging technology provides an abundance of spectral bands and a wider spectral bandwidth. This technique incorporates the potential to facilitate image‐guided surgery. It has, for example, been investigated for noninvasive intraoperative assessment of tissue oxygen saturation, intraoperative enhanced anatomical imaging and intraoperative assessment of resection margins for residual tumor tissue. Arrays of Charge‐Coupled Devices (CCD) and Complementary Metal Oxide Semiconductors (CMOS) are the most commonly used detectors (camera chips) in medical hyperspectral imaging systems, which can be composed of silicon (Si) and indium gallium arsenide (InGaAs) sensors. Si sensors cover the wavelength range of 400 – 1000 nm, whereas InGaAs sensors are typically sensitive in the 900 – 1700 nm wavelength region. As a first step to evaluate the potential of hyperspectral imaging in surgery, the spectral signatures of a variety of tissue types were explored for distinctive endogenous contrasts using DRS. Presently hyperspectral cameras with Si (covering the visible and near‐infrared wavelengths) and InGaAs (covering the extended near‐infrared and infrared range) sensor chips are becoming available. Therefore, we report investigations on including spectral distinctive features for these two sensor ranges. A first ex vivo exploration of DRS was described in Chapter 7. The wide‐band spectral properties of various tissue types were investigated in freshly explanted human colonic specimens: normal colonic tissue, tumorous tissue in the colon, mesenteric adipose tissue, arteries, veins and ureter. Translating the acquired spectra into clinically useful information by automated diagnostic algorithms is demonstrated for single spot data. The potential of such first (non‐imaging) DRS is the possibility to incorporate the technique in a hyperspectral imaging modality. In colorectal surgery detecting ureters and mesenteric arteries is of utmost importance to prevent iatrogenic injury and to facilitate intraoperative decision‐making. A tool enabling ureter‐ and artery‐specific image enhancement within surrounding adipose tissue would facilitate this need, especially during laparoscopy. Chapter 8 describes the use of DRS in open colorectal surgery for classification of ureter and artery in surrounding adipose tissue. To identify possible distinctive features for tissue classification, 36 features (i.e., 18 gradients and 18 amplitude differences at predefined points in the tissue spectra) were extracted based on known wavelengths related to characteristic absorption features for blood, water and fat. Gradients are “slopes” between two predefined points in the tissue spectra, i.e.: (DR2 – DR1)/(2 – 1). Amplitude differences are “intensity differences” between two predefined spectral 169
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