SAFARI

Shape Analysis For AI-Segmented Images

What is SAFARI

SAFARI (Shape Analysis For AI-Segmented Images) provides functionality for image processing and shape analysis. In the context of reconstructed medical images generated by deep learning-based methods and produced from different modalities such as X-ray, Computational Tomography (CT), Magnetic Resonance Imaging (MRI), and pathology imaging, SAFARI offers tools to segment regions of interest and extract quantitative shape descriptors for applications in signal processing, statistical analysis and modeling, and machine learning.

How SAFARI works

1. Upload Image

2. Run Analysis

3. Download Results

  • Type in required parameters and upload a binary image (PNG/GIF, <= 3MB) in which the white and black pixels make up the regions and background, respectively.
  • Minimum net area for filtering regions of interest and the number of regions to extract must be positive integers and cannot be simultaneously specified.

CITATION

Fern√°ndez, E., Yang, S., Chiou, S.H. et al. SAFARI: shape analysis for AI-segmented images. BMC Med Imaging 22, 129 (2022). https://doi.org/10.1186/s12880-022-00849-8

Online Analysis

Please read this document for the annotation in analysis
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Contact Us

Address


Department of Mathematical Sciences
The University of Texas at Dallas
800 W. Campbell Road
Richardson, TX 75080, United States