Cell Thresholder App

Main Features

1. Import Image

• How to Use:
  1. Drag and drop your image (JPEG, PNG) file into the application window.
  2. The image will load and be displayed on the screen for processing.

2. Import Mask from NPZ File

• How to Use:
  1. Drag and drop your NPZ file containing the mask data onto the application window.
  2. The NPZ file should contain the im_markers key with the mask data.
  3. Optionally, you can adjust the mask offset if required in the segment panel.
  4. The mask will be overlaid on the image to visualize the segmentation.

3. Preprocess Image with Rectangular or Circular Masks

• How to Use:
  • Rectangular (Label) Mask:
    1. Right-click anywhere on the image.
    2. Select "Label cut" from the context menu.
    3. Draw a rectangular area on the image by selecting two points to remove unwanted regions by excluding them from the analysis.
  • Circular Mask:
    1. Right-click anywhere on the image.
    2. Select "Circle mask" from the context menu.
    3. Draw a circular mask by selecting three points to eliminate regions outside the circle for cleaner analysis.

4. Segment the Image

• How to Use:
  1. Right-click anywhere on the image.
  2. Select "Segment" from the context menu.
  3. Set a Gaussian Blur kernel size to apply a Gaussian filter to the image before thresholding, improving segmentation results by reducing noise
  4. The Triangle Method will automatically segment the image by analyzing pixel intensity distributions.
  5. The resulting segmentation will be applied to the image.

5. Threshold the Image

• How to Use:
  1. Select a threshold value on the lower "Threshold" panel.
  2. Click "Apply" to execute the thresholding.
  3. Cells with an integral intensity lower than the selected threshold value will be excluded from the mask.

6. Export Processed Data to CSV

• How to Use:
  1. After completing the thresholding and masking steps, right-click on the image.
  2. Select "Export" from the context menu.
  3. Choose the location and filename for the CSV file.
  4. The app will export the following information:
     • Total Cell Count
     • Cell ID
     • Cell Area
     • Integral Intensity
  5. The CSV file will be saved with this data for further analysis.

Installation

1. Clone or download the repository to your local machine.

2. Install dependencies via pip:

   pip install -r requirements.txt

3. Run the application:

   python app.py

Alternatively, you can download the precompiled executable for windows from here and run it directly without needing to install Python or dependencies.

Requirements

• Python 3.6 or higher
• PyQt5
• OpenCV
• NumPy
• Scikit-image