Cell Analysis
| Application Type | Counting; Identification |
| Image Characteristics | Monochrome; Good Contrast; Noisy |
| Image Processing Tool(s) | Filtering; Thresholding |
The cell analysis example counts the number of cells and measures their areas using the Grayscale Filtering, Thresholding, and Binary Image Inversion functions.
Filters: Smoothing—Gaussian—Smoothes the image using a Gaussian filter.
Filters: Edge Detection—Laplacian—Highlights the edges in the image using a Laplacian filter. This operation finds edges in the filtered image and adds them to the original image. This operation helps increase the separation between the cells and the background.
Threshold: Auto Threshold—Metric—Separates the dark regions in the image from the rest of the image using an automatic threshold technique. In this case, the dark regions in the image correspond to the cells. The regions corresponding to the medium in which the cells are present appear as foreground in the resulting binary image.
Basic Morphology: Proper Close—Improves the shape of the particles in the binary image by smoothing the boundary of the particles, filling small holes in the particles, and closing small gaps along the perimeter of the particles.
Adv. Morphology: Fill Holes—Fills any size holes in a particle.
Particle Filter—Removes unwanted particles from the binary image using the particle filter. This application only analyzes particles that are mostly circular and larger than 10 pixels. Particles that have a Heywood Circularity Factor that falls outside of the 0 to 1.40 range or have a pixel area of less than 10 are removed.
Particle Analysis—Analyzes the properties of the remaining particles (cells) in the image. The particle measurement function can analyze up to 50 different properties of a particle.