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Automated and adaptable quantification of cellular alignment from microscopic images for tissue engineering
Feng Xu1, Turker Beyazoglu, Evan Hefner
1Demirci Bio-Acoustic-MEMS in Medicine (BAMM) Laboratory, Department of Medicine, Center for Biomedical Engineering , Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Tissue Engineering. Part C, Methods
|March 5, 2011
Summary
A new automated method, binarization-based extraction of alignment score (BEAS), accurately quantifies cellular alignment in engineered tissues. This tool aids in developing better biomaterials for tissue regeneration applications.
Area of Science:
- Biomaterials Science
- Tissue Engineering
- Image Analysis
Background:
- Cellular alignment is crucial for the function of tissues like muscle, nerve, and cornea.
- Regenerative medicine aims to replicate cellular microenvironments using biomaterials to guide cell alignment.
- Quantifying cellular alignment is essential for evaluating the success of engineered tissues.
Purpose of the Study:
- To develop a rapid, accurate, and adaptable automated method for quantifying cellular alignment.
- To address the need for improved methodologies in tissue engineering applications.
- To introduce the binarization-based extraction of alignment score (BEAS) method.
Main Methods:
- Developed an automated method (BEAS) using image processing techniques.
- Combined median and band-pass filters with locally adaptive thresholding.
- Obtained cellular alignment score from cell orientation distribution using a scoring algorithm.
Main Results:
- Validated the BEAS method against manual, FFT, and gradient-based approaches.
- Achieved statistically comparable alignment scores to the manual method (R²=0.92).
- Demonstrated the method's effectiveness across diverse microscopic images.
Conclusions:
- The BEAS method provides accurate and convenient evaluation of cellular alignment in engineered tissues.
- This automated approach facilitates the assessment of biomaterials for tissue engineering.
- BEAS enables adaptable evaluation of cellular organization in engineered constructs.
