With Panorama you create high-resolution overview images from individual images. The software puts the images together with pixel precision. The advantage: even images that have been acquired offset from each other can be joined precisely using ZEN and Panorama.
This means that important details from the individual images of your microscope specimen are recorded in a single image. A special feature here is that you can use the live image as a 'joystick' and therefore acquire the individual images even more quickly. Processing Images With these powerful additional modules you can display fluorescence signals with even greater contrast or visualize image stacks in 3 dimensions. ZEN therefore creates the best possible conditions for your experiments and publications.
The Colocalization module can be used to unmix the overlapping signals of different fluorescence channels. To do this, the ZEN software makes use of modern methods, such as the automated threshold value method of Costes et al. Meaningful results on the colocalization of proteins can be obtained as a scatter plot , image and data table.
If you only want to analyze certain areas of the image, you can simply mark the corresponding region directly in the image and scatter plot.
Spectral Colocalization for ZEN then supplies the data both for the whole image and the selected regions. Of course you can also export your measured values in CSV format and process them further using a spreadsheet. Due to the optical properties of the microscope system, light from the areas above and below the focal plane also enters the image.
This means that fine structures on the specimen can no longer be picked out. It is precisely here that the 3D Deconvolution software module starts, by calculating out of focus light back to its place of origin. The distorted specimen structure unfolds and is displayed more sharply. This technique also reduces any image noise that may be present, making a decisive contribution to the first-class image quality of your image stacks and 3D models. With 3Dxl you can display multi-dimensional image stacks in 3D.
Highlight is its ability to handle really large images hundreds of gigabyte efficiently and smoothly. You can position a three-dimensional model interactively according to the view that you require and provide it with annotations, coordinates and scaled axes. It goes without saying that 3Dxl also provides you with tools for the interactive measurement of distances and angles.
Would you like to present or publish the result afterwards? Analyzing and Interpreting Image Data ZEN provides important information on your microscope specimens interactively or fully automatically. Besides size and volume information, this also includes detailed data on cell physiological processes. Would you like to generate automatic measurement procedures simply yourself? The ZEN Image Analysis module makes it possible for you to do this, even without programming knowledge.
With our measurement program wizard you tackle even complex measurement tasks yourself in just a few minutes. Once created, the programs are always available to be used for an unlimited number of images.
You retain full control over the measurement process at all times. Each step can be changed interactively before it is performed. Whilst this method is easy to use and gives excellent results it is important to be aware that several steps may require a long processing time minutes , especially on large images.
As the algorithm relies on local intensity contrast to trace filaments the use of a image filter will reduce noise and minimise tracing errors. For most cases, applying a median filter found under under Image Processing before starting the filament workflow will ensure best results. If you intend to accurately count spines it is recommended to deconvolve your image first using Autoquant available on Imaris Workstation 1. Choose the AutoPath no loops algorithm in the drop down menu.
This algorithm prevents looping back on neuronal processes. Since this algorithm relies on local intensity contrast to trace the filaments use of a filter Gaussian Filtering , under Image Processing will reduce noise and minimize tracing errors.
Also select calculate diameter of filaments from image is enabled. Then press the blue arrow to go on to the next step. NOTE: If you intend to accurately count spines it is recommended to deconvolve your image first using Huygens Deconvolution.
If you only wish to trace one neuron in an image that contains several use a region of interest to save time. Test code is written in simple English called Gherkin. Cucumber code can be executed on different frameworks like Selenium, Ruby, etc. Skip to content. Report a Bug. Previous Prev. Next Continue. Home Testing Expand child menu Expand. SAP Expand child menu Expand. Web Expand child menu Expand. Must Learn Expand child menu Expand. Big Data Expand child menu Expand.
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