Name
Abstract | ||
|---|---|---|
Efficient processing of 3D image data is one of the biggest challenges in biological image analysis. Single plane illumination microscopy, for instance, allows acquiring massive amounts of 3D image data that needs to be processed automatically. An important preprocessing step is deconvolution which reduces the image blur introduced by the imaging system. An often used algorithm is Richardson-Lucy deconvolution which, however, is very time-consuming for huge amounts of 3D image data. We have developed an FPGA-based acceleration of Richardson-Lucy deconvolution. Compared to CPU architectures the computation time is reduced. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ISBI.2016.7493228 | 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) |
Keywords | Field | DocType |
3D deconvolution,field-programmable gate array (FPGA),heterogeneous system,preprocessing of 3D image data | Computer vision,Richardson–Lucy deconvolution,Computer science,Field-programmable gate array,Deconvolution,Preprocessor,Artificial intelligence,Acceleration,3d image,Computation | Conference |
ISSN | Citations | PageRank |
1945-7928 | 2 | 0.38 |
References | Authors | |
4 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Bromberger | 1 | 4 | 2.11 |
| Pascal Bastian | 2 | 2 | 0.38 |
| Jan-Philip Bergeest | 3 | 33 | 3.39 |
| Christian Conrad | 4 | 2 | 0.38 |
| Vincent Heuveline | 5 | 179 | 30.51 |
| Karl Rohr | 6 | 27 | 2.05 |
| Wolfgang Karl | 7 | 46 | 6.44 |