Heat maps are a visual representation of data where each point in a two-dimensional space is assigned a color based on a numerical value. They are often used to visualize spatial data, such as the distribution of a particular feature across an image or a map. In the context of Whole Slide Images (WSIs) in the .svs format, heat maps can be used to represent the distribution of cells, proteins, or other features of interest.

To generate a heat map on a WSI using probability values, the following steps can be taken:

1. Obtain the probability values: The probability values can be obtained through various methods such as image analysis algorithms, machine learning models or manually annotated data.

2. Define the regions of interest: Based on the specific feature of interest, regions of interest can be defined on the WSI. These regions can be defined manually or through automated segmentation algorithms.

3. Map the probability values to the regions of interest: Once the regions of interest are defined, the probability values can be mapped to each region. For example, the mean probability value can be calculated for each region.

4. Generate the heat map: Finally, the heat map can be generated by assigning a color to each region based on its probability value. A color scale can be chosen to represent the range of probability values, with hot colors such as red representing high probability and cool colors such as blue representing low probability.

There are various software tools available for generating heat maps on WSIs, such as ImageScope, QuPath, and Aperio eSlide Manager. These tools provide various options for customizing the heat map, such as adjusting the color scale, adding annotations, and exporting the image in different formats.