A Workflow for Rapid Unbiased Quantification of Fibrillar Feature Alignment in Biological Images
Measuring the organization of the cellular cytoskeleton and the surrounding extracellular matrix (ECM) is currently of wide interest as changes in both local and global alignment can highlight alterations in cellular functions and material properties of the extracellular environment. Different appro...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-10-01
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| Series: | Frontiers in Computer Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcomp.2021.745831/full |
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| author | Stefania Marcotti Deandra Belo de Freitas Lee D Troughton Fiona N Kenny Tanya J Shaw Brian M Stramer Patrick W Oakes |
| author_facet | Stefania Marcotti Deandra Belo de Freitas Lee D Troughton Fiona N Kenny Tanya J Shaw Brian M Stramer Patrick W Oakes |
| author_sort | Stefania Marcotti |
| collection | DOAJ |
| description | Measuring the organization of the cellular cytoskeleton and the surrounding extracellular matrix (ECM) is currently of wide interest as changes in both local and global alignment can highlight alterations in cellular functions and material properties of the extracellular environment. Different approaches have been developed to quantify these structures, typically based on fiber segmentation or on matrix representation and transformation of the image, each with its own advantages and disadvantages. Here we present AFT − Alignment by Fourier Transform, a workflow to quantify the alignment of fibrillar features in microscopy images exploiting 2D Fast Fourier Transforms (FFT). Using pre-existing datasets of cell and ECM images, we demonstrate our approach and compare and contrast this workflow with two other well-known ImageJ algorithms to quantify image feature alignment. These comparisons reveal that AFT has a number of advantages due to its grid-based FFT approach. 1) Flexibility in defining the window and neighborhood sizes allows for performing a parameter search to determine an optimal length scale to carry out alignment metrics. This approach can thus easily accommodate different image resolutions and biological systems. 2) The length scale of decay in alignment can be extracted by comparing neighborhood sizes, revealing the overall distance that features remain anisotropic. 3) The approach is ambivalent to the signal source, thus making it applicable for a wide range of imaging modalities and is dependent on fewer input parameters than segmentation methods. 4) Finally, compared to segmentation methods, this algorithm is computationally inexpensive, as high-resolution images can be evaluated in less than a second on a standard desktop computer. This makes it feasible to screen numerous experimental perturbations or examine large images over long length scales. Implementation is made available in both MATLAB and Python for wider accessibility, with example datasets for single images and batch processing. Additionally, we include an approach to automatically search parameters for optimum window and neighborhood sizes, as well as to measure the decay in alignment over progressively increasing length scales. |
| first_indexed | 2024-12-17T12:11:45Z |
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| id | doaj.art-7c9b8a37505347c8ba8e87de3b3459cb |
| institution | Directory Open Access Journal |
| issn | 2624-9898 |
| language | English |
| last_indexed | 2024-12-17T12:11:45Z |
| publishDate | 2021-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Computer Science |
| spelling | doaj.art-7c9b8a37505347c8ba8e87de3b3459cb2022-12-21T21:49:22ZengFrontiers Media S.A.Frontiers in Computer Science2624-98982021-10-01310.3389/fcomp.2021.745831745831A Workflow for Rapid Unbiased Quantification of Fibrillar Feature Alignment in Biological ImagesStefania Marcotti0Deandra Belo de Freitas1Lee D Troughton2Fiona N Kenny3Tanya J Shaw4Brian M Stramer5Patrick W Oakes6Randall Centre for Cell and Molecular Biophysics, King’s College London, London, United KingdomRandall Centre for Cell and Molecular Biophysics, King’s College London, London, United KingdomDepartment of Cell and Molecular Physiology, Stritch School of Medicine, Loyola University Chicago, Maywood, IL, United StatesRandall Centre for Cell and Molecular Biophysics, King’s College London, London, United KingdomCentre for Inflammation Biology & Cancer Immunology, King’s College London, London, United KingdomRandall Centre for Cell and Molecular Biophysics, King’s College London, London, United KingdomDepartment of Cell and Molecular Physiology, Stritch School of Medicine, Loyola University Chicago, Maywood, IL, United StatesMeasuring the organization of the cellular cytoskeleton and the surrounding extracellular matrix (ECM) is currently of wide interest as changes in both local and global alignment can highlight alterations in cellular functions and material properties of the extracellular environment. Different approaches have been developed to quantify these structures, typically based on fiber segmentation or on matrix representation and transformation of the image, each with its own advantages and disadvantages. Here we present AFT − Alignment by Fourier Transform, a workflow to quantify the alignment of fibrillar features in microscopy images exploiting 2D Fast Fourier Transforms (FFT). Using pre-existing datasets of cell and ECM images, we demonstrate our approach and compare and contrast this workflow with two other well-known ImageJ algorithms to quantify image feature alignment. These comparisons reveal that AFT has a number of advantages due to its grid-based FFT approach. 1) Flexibility in defining the window and neighborhood sizes allows for performing a parameter search to determine an optimal length scale to carry out alignment metrics. This approach can thus easily accommodate different image resolutions and biological systems. 2) The length scale of decay in alignment can be extracted by comparing neighborhood sizes, revealing the overall distance that features remain anisotropic. 3) The approach is ambivalent to the signal source, thus making it applicable for a wide range of imaging modalities and is dependent on fewer input parameters than segmentation methods. 4) Finally, compared to segmentation methods, this algorithm is computationally inexpensive, as high-resolution images can be evaluated in less than a second on a standard desktop computer. This makes it feasible to screen numerous experimental perturbations or examine large images over long length scales. Implementation is made available in both MATLAB and Python for wider accessibility, with example datasets for single images and batch processing. Additionally, we include an approach to automatically search parameters for optimum window and neighborhood sizes, as well as to measure the decay in alignment over progressively increasing length scales.https://www.frontiersin.org/articles/10.3389/fcomp.2021.745831/fullalignmentfast Fourier transform (FFT)cytoskeletonextracellular matrix (ECM)fibersanisotropy |
| spellingShingle | Stefania Marcotti Deandra Belo de Freitas Lee D Troughton Fiona N Kenny Tanya J Shaw Brian M Stramer Patrick W Oakes A Workflow for Rapid Unbiased Quantification of Fibrillar Feature Alignment in Biological Images Frontiers in Computer Science alignment fast Fourier transform (FFT) cytoskeleton extracellular matrix (ECM) fibers anisotropy |
| title | A Workflow for Rapid Unbiased Quantification of Fibrillar Feature Alignment in Biological Images |
| title_full | A Workflow for Rapid Unbiased Quantification of Fibrillar Feature Alignment in Biological Images |
| title_fullStr | A Workflow for Rapid Unbiased Quantification of Fibrillar Feature Alignment in Biological Images |
| title_full_unstemmed | A Workflow for Rapid Unbiased Quantification of Fibrillar Feature Alignment in Biological Images |
| title_short | A Workflow for Rapid Unbiased Quantification of Fibrillar Feature Alignment in Biological Images |
| title_sort | workflow for rapid unbiased quantification of fibrillar feature alignment in biological images |
| topic | alignment fast Fourier transform (FFT) cytoskeleton extracellular matrix (ECM) fibers anisotropy |
| url | https://www.frontiersin.org/articles/10.3389/fcomp.2021.745831/full |
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