Fluorescence Tracker App
Updated 13 Apr 2022
This app uses computer vision point tracking to quantify near infrared signals emitted by (ICG) Indocyanine Green during fluorescence angiography. A quick overview of how this app works can be seen in the following 4-minute video: How to Detect and Track Features in a Video.
The following research in colorectal cancer was carried out using this software: "Digital Dynamic Discrimination of Primary Colorectal Cancer using Systemic Indocyanine Green with Near-infrared Endoscopy" by Jeffrey Dalli et al., UCD Centre for Precision Surgery, School of Medicine, University College Dublin, Ireland (2021).
This research is also highlighted in the article "Automating Endoscopic Tissue Characterization in Cancer Patients with Computer Vision".
- MATLAB R2020b (or newer)
- Image Processing Toolbox, Computer Vision Toolbox, and Statistics and Machine Learning Toolbox
- Please see the Fluorescence Tracker App User Guide for video format requirements
FeatureTrackingUsingKLTExample.mlxis a reference example independent of the Fluorescence Tracker App
- Download/navigate to the installer file (Fluorescence Tracker.mlappinstall)
- Double-click on the installer file
- Click "Install" when prompted in MATLAB
- The app will then appear in the APPS tab in MATLAB
- The app source code can then be found in the installation folder specified by your MATLAB Add-Ons Preferences (or by querying the app installation location)
- Please see the Fluorescence Tracker App User Guide for more information
- Overview of MATLAB Apps
- App Building with MATLAB
- Feature Detection and Extraction with MATLAB
- Tracking and Motion Estimation with MATLAB
Paul Huxel (2022). Fluorescence Tracker App (https://github.com/mathworks/Fluorescence-Tracker-App/releases/tag/v1.6), GitHub. Retrieved .
MATLAB Release Compatibility
Platform CompatibilityWindows macOS Linux
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