Free Online Tool for cell counting
Introduction
OnCellCounter™ is a web-based cell counter tool that provides cell counting and cell viability analysis for user-uploaded images. Developed by Logos Biosystems, a company specializing in automated cell counters, OnCellCounter™ delivers accurate and reliable cell counting results.
How to Use OnCellCounter™
Using OnCellCounter™ is easy and involves just three simple steps:
Step 1: Image Upload
Click the “Open” button at the top of OnCellCounter™ to upload the image you want to use for cell counting. OnCellCounter™ supports most image formats. If you are unable to upload the image, try renaming the file using only English letters and numbers, then upload it again.
Step 2: Cell Marking
Click the “Rectangle” button at the top of OnCellCounter™ and mark a representative cell in the image. Use the mouse scroll to zoom in or out on the image. For best results, ensure the rectangular boundary closely follows the exact outline of the selected cell. If the rectangle is too large or small, the counting results may be inaccurate.
Step 3: Count
Click the “Count” button to perform cell counting.
How to optimize the protocol
OnCellCounter™ allows users to optimize protocols for more accurate cell counting results. The protocol in OnCellCounter™ consists of five parameters: Min. and Max. Search Size, Cell Detection Sensitivity, Live Cell Sensitivity, and Noise Reduction.
1. Min. Search Size
The Min. Search Size refers to the smallest cell size that OnCellCounter™ will attempt to detect in an image. Unlike size gating, which filters out cells based on specific size, the Min. Search Size represents an “approximate” cell size used to screen cell-like objects. As a result, cells slightly smaller than the Min. Search Size may still be counted.
When you use the Rectangle tool to mark a cell, the Min. Search Size is automatically set based on the marked cell. However, you can adjust this value manually to optimize cell detection if needed.
The PBMCs in the image have an average size of 14 pixels. In this case, a Min. Search Size of 8.4 pixels, which is 60% of the average size, is an appropriate value. If a value smaller than this is entered, the software may detect small background particles. Conversely, entering a value that is too large may prevent the detection of the cells.
2. Max. Search Size
The Max. Search Size refers to the largest cell size that OnCellCounter™ will attempt to detect in an image. Similar to the Min. Search Size, the Max. Search Size is not a size gating parameter but rather an approximate cell size used as a reference for identifying cells.
When you use the Rectangle tool to mark a cell, the Max. Search Size is automatically set based on the marked cell. However, you can manually adjust this value to set a limit the size of largest objects to be detected.
3. Cell Detection Sensitivity
The Cell Detection Sensitivity parameter can be adjusted to either detect more cells or exclude unwanted objects. Increasing the sensitivity allows OnCellCounter™ to identify more objects as cells, while lowering the sensitivity applies stricter conditions for cell detection.
Additionally, increasing the sensitivity enhances declustering, making it more effective at separating clustered cells.
If the desired cells are not being detected properly, consider increasing the sensitivity value.
Cell Detection Sensitivity can also be used to adjust the level of cell de-clustering. Increasing the Cell Detection Sensitivity allows the detection of more individual cells within a cluster. However, this may also result in the detection of faint debris in the background. To enhance the de-clustering level while simultaneously removing background noise, adjust both the Cell Detection Sensitivity and Noise Reduction parameters to achieve the optimal results.
The image is from a validation slide for automated cell counters (Cat# L72041, Logos Biosystems), featuring a printed pattern of regular live and dead cells. The dust present in the center of the image has distinct features that differentiate it from the background, causing it to be detected as a dead cell under the default protocol settings. In this case, you can lower the Cell Detection Sensitivity to exclude the dust from being identified as a cell.
4. Live Cell Sensitivity
Live Cell Sensitivity is a parameter used to distinguish between live and dead cells. Increasing this value increases the number of live cells detected, while decreasing it reduces the number of live cells identified.
These cells are trypan blue-stained PBMCs captured at low magnification, resulting in small cell sizes where the bright spot in the center is not clearly visible. The two cells on the left can be classified as either live or dead, depending on the parameters. In such cases, you can adjust the Live Cell Sensitivity to classify the same cells as either live or dead.
5. Noise Reduction
Noise Reduction is used to include or exclude faint objects present in the background of an image. Lowering the noise reduction setting allows OnCellCounter™ to include more faint objects. Conversely, increasing the noise reduction setting excludes faint objects such as cell debris.
The cell in the center of the image is less stained compared to other cells, making it likely to be classified as a dead cell or long-degraded debris. In such cases, you can adjust the Noise Reduction value to either include or exclude it from the cell count.
Available Cell Counters, please visit wisbiomed.com