Hyperspectral imaging is a promising clinical imaging modality with multiple applications in wound care, dermatology, and ophthalmology. However, with current technologies, hyperspectral imagers are relatively large and expensive devices, mainly affordable only by hospitals. Multispectral imaging can be a cost-effective alternative for hyperspectral imaging and is capable of bringing diagnostics to primary health care. Multispectral imaging uses known features of tissue chromophores to simplify imaging device design. However, to maintain design simple and cost-effective the number of illumination bands should be minimal. Thus, proper band selection is very important. The goal of the current study is to develop an analytical model for the optimization of band selection for multispectral and narrow-band imaging techniques (e.g., narrow-band microscopy).
Methods: The contrast ratio has been proposed for quantification of image quality of subsurface inhomogeneities in the skin. Based on the two-flux Kubelka-Munk model, we developed an analytical approach which links the contrast ratio with optical tissue parameters.
Results: We obtained an explicit analytical solution for the dependence of maximal contrast ratio on optical tissue parameters. Then, we linked the minimally observable contrast ratio (cmin) with the bit depth of the camera, d: cmin = 1/(2d-1). Based on this analysis we were able to derive an explicit expression, which links camera properties with the minimally detectable changes in optical tissue parameters (both scattering and absorption).
Conclusions: The proposed analytical model can be used for rapid assessment and optimization of multispectral and narrow band imaging techniques and for estimation of the accuracy of imaging techniques. The developed model confirms the utility of the contrast ratio for tissue imaging.
Keywords: Biomedical imaging; Blood vessels; Contrast ratio; Multispectral imaging.