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Quantification of fluorescence signals from 800CW-labelled tumour tissue

Schmidt, I. (2018) Quantification of fluorescence signals from 800CW-labelled tumour tissue.

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Abstract:The aim of this study is to improve quantification of the measured fluorescence signal in surgical specimen to acquire a more objective observation of the fluorescence intensity and ultimately, make a clear distinction between tumorous and non-tumorous tissue. The primary objective of this study is to determine the feasibility of two quantification methods to make a clearer distinction between tumorous and non-tumorous tissue, by correcting the fluorescence signal for influences of illumination differences and tissue optical properties. Two correction methods are applied: a ratiometric correction method and space-variant deconvolution. For the ratiometric correction, a phantom is used for the validation for the correction for both the black box and intraoperative camera. Next, the correction method is applied to tissue images made with the black box. The space-variant deconvolution method is applied to both a mathematical phantom and black box images of tissue. Both methods show an improvement of the fluorescence detection. For the ratiometric correction, an improvement was visible for the phantom and the two tissue types, although the extent of the improvement differed between the three, due to image acquisition. This method could be applied clinically and improve clinical decision making based on fluorescent images. The results for the spatially-variant deconvolution showed that the method could improve fluorescence imaging, but involves multiple assumptions which could introduce inaccuracies in the resulting images. Therefore, the ratiometric correction proved to be a more solid correction method with short acquisition time compared to the spatially-variant deconvolution method. Additionally, the ratiometric correction would be easier to apply in a clinical, real time setting. For clinical incorporation, simultaneously acquired fluorescence and excitation images with automatic or predefined settings for polarization are crucial.
Item Type:Essay (Master)
Faculty:TNW: Science and Technology
Subject:44 medicine
Programme:Technical Medicine MSc (60033)
Link to this item:https://purl.utwente.nl/essays/74735
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