Ünay D.Stanciu S.G.2023-06-162023-06-1620189.78E+12https://doi.org/10.1109/SIU.2018.8404623https://hdl.handle.net/20.500.14365/3612Aselsan;et al.;Huawei;IEEE Signal Processing Society;IEEE Turkey Section;Netas26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 2 May 2018 through 5 May 2018 -- 137780Confocal laser scanning microscopy relies on illuminating the specimen with a focused scanning laser beam and constructing sharp optical sections/images of the investigated specimen by allowing signals from the focal plane only via a pinhole. It is a valuable technique to study fluorescent cells and tissues in-vivo. Its power and potential can be augmented by the use of computer vision methods. However such methods are typically transferred to the microscopy field directly without taking microscopy-specific variations into account. Accordingly in this study we evaluate the robustness of SIFT feature descriptors, a popular computer vision method, against variations in microscopy-specific parameters over a benchmark dataset acquired in a principled manner. Results show that SIFT descriptors are highly robust against variations in laser beam power, whereas their robustness diminishes with larger variations in photomultiplier tube gain. © 2018 IEEE.trinfo:eu-repo/semantics/closedAccessConfocal laser scanning microscopyFeature descriptorHistopathologyImaging parametersRobustnessSIFTComputer visionConfocal microscopyLaser applicationsLaser beamsPhotomultipliersRobustness (control systems)Confocal laser scanning microscopyFeature descriptorsHistopathologyImaging parametersSIFTScanningConference Object10.1109/SIU.2018.84046232-s2.0-85050804277