Cell Movement and Morphology Analysis

Tracking cell movement and changes in shape using microscopy images and computer vision. ENGR 1050 (Scientific Computing).

Overview

I wrote an image-analysis workflow to track cells in time-lapse microscopy. It measures how far cells move and how their area and brightness change, making it easier to compare behavior across experimental conditions.

Project notebook

Methods

  • Image preprocessing: Converting .tif images to grayscale and applying thresholding to segment cells from background noise.
  • Feature extraction (OpenCV): Drawing contours, measuring changes in cell area & brightness intensity, and calculating cell centroids.
  • Movement analysis: Tracking centroid displacement over time and measuring relative changes in area and brightness between time points.
  • Automation: Implemented batch analysis for multiple cell images across two cell types, exported results to Excel for downstream analysis, and implemented unit tests for validation.

Results

The workflow produced cell-velocity measurements and tracked changes in area and brightness across the image sequences.

Image after grayscaling and thresholding for segmentation (left) and after drawing a contour (right).

Skills Used

  • Programming: OpenCV, Pandas, NumPy