This technical note presents a rapid data analysis method for differential mobility cytometry (DMC), which is a technique used to capture cells and study adhesion processes. DMC uses an oscillating flow field to maintain a finite number of cells in a microfluidic device and records video data of cells oscillating back and forth. As cells impact the affinity surface, they can form bonds with the surface, leading to immobilization or leaving the surface. The speed of each cell and the capture time can be recorded using frame difference measurements from video data. Previously, data analysis involved manual manipulation of video files, which was time-consuming and limited throughput. To address this, a rapid, automated data analysis protocol has been developed using ImageJ software. This method involves subtracting short movies from each other to create a stack of differential images that can be easily analyzed. The goal of this technical note is to make DMC more accessible through a simplified and high-throughput data analysis approach. The method involves recording video data, compressing it into mpeg-4 format, and importing it into ImageJ. The video is then split into two stacks of frames, with a certain number of frames removed from each. The two stacks are then subtracted to reveal the mobility difference of the cells. The mobility difference of target cells is calculated by drawing an analysis window around each cell of interest and measuring the mobility difference. This method allows for the efficient analysis of large numbers of cells over long timescales, improving the throughput of DMC. The results show that immobile cells have a mobility difference of zero, while mobile cells have a higher mobility difference. This method provides a more efficient and automated way to analyze DMC data, making it more accessible for research and clinical applications.This technical note presents a rapid data analysis method for differential mobility cytometry (DMC), which is a technique used to capture cells and study adhesion processes. DMC uses an oscillating flow field to maintain a finite number of cells in a microfluidic device and records video data of cells oscillating back and forth. As cells impact the affinity surface, they can form bonds with the surface, leading to immobilization or leaving the surface. The speed of each cell and the capture time can be recorded using frame difference measurements from video data. Previously, data analysis involved manual manipulation of video files, which was time-consuming and limited throughput. To address this, a rapid, automated data analysis protocol has been developed using ImageJ software. This method involves subtracting short movies from each other to create a stack of differential images that can be easily analyzed. The goal of this technical note is to make DMC more accessible through a simplified and high-throughput data analysis approach. The method involves recording video data, compressing it into mpeg-4 format, and importing it into ImageJ. The video is then split into two stacks of frames, with a certain number of frames removed from each. The two stacks are then subtracted to reveal the mobility difference of the cells. The mobility difference of target cells is calculated by drawing an analysis window around each cell of interest and measuring the mobility difference. This method allows for the efficient analysis of large numbers of cells over long timescales, improving the throughput of DMC. The results show that immobile cells have a mobility difference of zero, while mobile cells have a higher mobility difference. This method provides a more efficient and automated way to analyze DMC data, making it more accessible for research and clinical applications.