Views provided by UsageCounts
To evaluate our results we constructed an automated image processing software. The program is called Line Profiler and is available as executable on: Zenodo… In a first step Line Profiler uses several image processing algorithms to select potential regions of interest. The SNC Helix structure is spotted by detecting closed shapes in the image. This is achieved by blurring the image with a nxn Gaussian Kernel, to account for potential holes in the line. A threshold algorithm converts the grayscale to a binary image. A floodfill algorithm leaves only the areas embedded in closed shapes. The maximum value of a distance Transformation reveals the candidate points where the helix structure is in plain. The direction of the applied line profile is determined by the gradient direction arctan(SobelX, SobelY) of the edge point closest to the preselected candidate point.
Executable, Synaptonemal Complex, Super-resolution, Expansion microscopy, Structured ilumination, User Interface, Edge Detection
Executable, Synaptonemal Complex, Super-resolution, Expansion microscopy, Structured ilumination, User Interface, Edge Detection
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 2 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 9 |

Views provided by UsageCounts