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Optical differentiation is a promising tool in biomedical diagnosis mainly because of its safety. The optical parameters' values of biological tissues differ according to the histopathology of the tissue and hence could be used for differentiation. The optical fluence rate distribution on tissue boundaries depends on the optical parameters. So, providing image displays of such distributions can provide a visual means of biomedical diagnosis. In this work, an experimental setup was implemented to measure the spatially-resolved steady state diffuse reflectance and transmittance of native and coagulated chicken liver and native and boiled breast chicken skin at 635 and 808 nm wavelengths laser irradiation. With the measured values, the optical parameters of the samples were calculated in vitro using a combination of modified Kubelka-Munk model and Bouguer-Beer-Lambert law. The estimated optical parameters values were substituted in the diffusion equation to simulate the fluence rate at the tissue surface using the finite element method. Results were verified with Monte-Carlo simulation. The results obtained showed that the diffuse reflectance curves and fluence rate distribution images can provide discrimination tools between different tissue types and hence can be used for biomedical diagnosis.

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Background The common formation of images in CSLM assumes mechanically scanned object placed in the common short focus of the objective lenses of the microscope, while in the arrangement under study, the scanning of the object is realized by placing a diffuser behind the collimating lens. A model is suggested in the formation of images in Confocal Scanning Laser Microscope (CSLM) using non-scanned object. Since the illumination and detection are coherent, the obtained image is constructed from the simple product of the Resultant Point Spread Function (RPSF) modulated by the diffuser spread over the object transparency. Hence, the product of the object and the image of the diffuser replace the mechanical scanning of the object. Results Reconstructed images using this novel arrangement of CNSM are presented using mammographic X-ray image. Conclusions Convolution of the RPSF and the object is realized by the spreading of the diffuser image over the object. A coherent detector captures the whole image affected by a noisy diffused function. It is noted that image processing is necessary to improve noisy images making use of filtration techniques.