9 July 2015 Improved cancer diagnostics by different image processing techniques on OCT images
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Abstract
Optical-coherence tomography (OCT) is a promising non-invasive, high-resolution imaging modality which can be used for cancer diagnosis and its therapeutic assessment. However, speckle noise makes detection of cancer boundaries and image segmentation problematic and unreliable. Therefore, to improve the image analysis for a precise cancer border detection, the performance of different image processing algorithms such as mean, median, hybrid median filter and rotational kernel transformation (RKT) for this task is investigated. This is done on OCT images acquired from an ex-vivo human cancerous mucosa and in vitro by using cultivated tumour applied on organotypical hippocampal slice cultures. The preliminary results confirm that the border between the healthy and the cancer lesions can be identified precisely. The obtained results are verified with fluorescence microscopy. This research can improve cancer diagnosis and the detection of borders between healthy and cancerous tissue. Thus, it could also reduce the number of biopsies required during screening endoscopy by providing better guidance to the physician.
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Rajesh Kanawade, Rajesh Kanawade, Benjamin Lengenfelder, Benjamin Lengenfelder, Tassiana Marini Menezes, Tassiana Marini Menezes, Martin Hohmann, Martin Hohmann, Stefan Kopfinger, Stefan Kopfinger, Tim Hohmann, Tim Hohmann, Urszula Grabiec, Urszula Grabiec, Florian Klämpfl, Florian Klämpfl, Jean Gonzales Menezes, Jean Gonzales Menezes, Maximilian Waldner, Maximilian Waldner, Michael Schmidt, Michael Schmidt, } "Improved cancer diagnostics by different image processing techniques on OCT images", Proc. SPIE 9541, Optical Coherence Imaging Techniques and Imaging in Scattering Media, 95410J (9 July 2015); doi: 10.1117/12.2183838; https://doi.org/10.1117/12.2183838
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