Application of MATLAB-Based Watershed Algorithm in Segmentation of Adherent Cell Images

In cell image segmentation, the adhesive effects between cells often present challenges for accurate separation. To address this issue, we employ a MATLAB-based watershed algorithm for image processing. This algorithm treats the image as a topographical surface, partitioning it into distinct regions through gradient magnitude calculations and marker-controlled watershed transformations. For cell images, this approach enables effective separation between cells and background using functions like imgradient() for gradient computation and watershed() for region segmentation. The implementation typically involves preprocessing steps such as noise reduction using imfilter() and distance transform via bwdist() to identify cell centers as markers. Consequently, the watershed algorithm proves to be a highly practical tool in cell image segmentation, facilitating improved analysis of cellular morphology and behavior through automated boundary detection and region labeling capabilities.