Name
Title | ||
|---|---|---|
Robustness of sift feature descriptors to imaging parameters in laser scanning microscopy. |
Abstract | ||
|---|---|---|
Confocal 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. |
Year | Venue | Keywords |
|---|---|---|
2018 | Signal Processing and Communications Applications Conference | SIFT,Feature descriptor,Confocal laser scanning microscopy,Histopathology,Imaging parameters,Robustness |
Field | DocType | ISSN |
Scale-invariant feature transform,Computer vision,Optical microscope,Cardinal point,Computer science,Optics,Robustness (computer science),Laser,Artificial intelligence,Microscopy,Photomultiplier,Laser beams | Conference | 2165-0608 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Devrim Ünay | 1 | 1 | 1.04 |
| stefan g stanciu | 2 | 5 | 6.90 |