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Near Infrared Diffuse Optical Tomography has the potential to be used as a non-invasive imaging tool for biological tissue specifically for the diagnosis and characterization of breast cancer. Most model based reconstruction algorithms rely on calculating and inverting a large Jacobian matrix. Although this method is flexible for a wide range of complex problems, it usually results in large image artifacts from hypersensitivity around the detectors. In this work a Jacobian normalization technique is presented which takes into account the varying magnitude of different optical parameters creating a more uniform update within a spectral image reconstruction model. Using simulated data the Jacobian normalization method is used to reconstructed images of absolute chromophore and scattering parameters which are qualitatively and quantitatively as compared to conventional methods. The hypersensitivity resulting in boundary artifacts are shown to be minimized with only a small additional computational cost.

Wavelength dependence of sensitivity in spectral diffuse optical imaging: effect of normalization on image reconstruction