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The filament sensor for near real-time detection of cytoskeletal fiber structures.

Eltzner B, Wollnik C, Gottschlich C, Huckemann S, Rehfeldt F - PLoS ONE (2015)

Bottom Line: Further, we provide a benchmark dataset of real cell images along with filaments manually marked by a human expert as well as simulated benchmark images.The FS clearly outperforms existing methods in terms of computational runtime and filament extraction accuracy.The implementation of the FS and the benchmark database are available as open source.

View Article: PubMed Central - PubMed

Affiliation: Institute for Mathematical Stochastics, Georg-August-University, 37077 Göttingen, Germany.

ABSTRACT
A reliable extraction of filament data from microscopic images is of high interest in the analysis of acto-myosin structures as early morphological markers in mechanically guided differentiation of human mesenchymal stem cells and the understanding of the underlying fiber arrangement processes. In this paper, we propose the filament sensor (FS), a fast and robust processing sequence which detects and records location, orientation, length, and width for each single filament of an image, and thus allows for the above described analysis. The extraction of these features has previously not been possible with existing methods. We evaluate the performance of the proposed FS in terms of accuracy and speed in comparison to three existing methods with respect to their limited output. Further, we provide a benchmark dataset of real cell images along with filaments manually marked by a human expert as well as simulated benchmark images. The FS clearly outperforms existing methods in terms of computational runtime and filament extraction accuracy. The implementation of the FS and the benchmark database are available as open source.

No MeSH data available.


Related in: MedlinePlus

Challenges for filament extraction.(a) blur (detail from image VB2) The overall contrast of the cell body is very low and lines are hardly discernible. (b) overexposure and noise (B2) The extensive regions of maximal brightness hide any structure that may be present in those regions. Salt and pepper noise is clearly visible as dark spots in bright areas and bright spots in dark areas. (c) filament crossings (M3). A bundle of roughly vertical filaments of varying brightness crosses a bundle of roughly horizontal filaments with varying brightness.
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pone.0126346.g002: Challenges for filament extraction.(a) blur (detail from image VB2) The overall contrast of the cell body is very low and lines are hardly discernible. (b) overexposure and noise (B2) The extensive regions of maximal brightness hide any structure that may be present in those regions. Salt and pepper noise is clearly visible as dark spots in bright areas and bright spots in dark areas. (c) filament crossings (M3). A bundle of roughly vertical filaments of varying brightness crosses a bundle of roughly horizontal filaments with varying brightness.

Mentions: III) all filament features: location, length, width and orientation;


The filament sensor for near real-time detection of cytoskeletal fiber structures.

Eltzner B, Wollnik C, Gottschlich C, Huckemann S, Rehfeldt F - PLoS ONE (2015)

Challenges for filament extraction.(a) blur (detail from image VB2) The overall contrast of the cell body is very low and lines are hardly discernible. (b) overexposure and noise (B2) The extensive regions of maximal brightness hide any structure that may be present in those regions. Salt and pepper noise is clearly visible as dark spots in bright areas and bright spots in dark areas. (c) filament crossings (M3). A bundle of roughly vertical filaments of varying brightness crosses a bundle of roughly horizontal filaments with varying brightness.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4440737&req=5

pone.0126346.g002: Challenges for filament extraction.(a) blur (detail from image VB2) The overall contrast of the cell body is very low and lines are hardly discernible. (b) overexposure and noise (B2) The extensive regions of maximal brightness hide any structure that may be present in those regions. Salt and pepper noise is clearly visible as dark spots in bright areas and bright spots in dark areas. (c) filament crossings (M3). A bundle of roughly vertical filaments of varying brightness crosses a bundle of roughly horizontal filaments with varying brightness.
Mentions: III) all filament features: location, length, width and orientation;

Bottom Line: Further, we provide a benchmark dataset of real cell images along with filaments manually marked by a human expert as well as simulated benchmark images.The FS clearly outperforms existing methods in terms of computational runtime and filament extraction accuracy.The implementation of the FS and the benchmark database are available as open source.

View Article: PubMed Central - PubMed

Affiliation: Institute for Mathematical Stochastics, Georg-August-University, 37077 Göttingen, Germany.

ABSTRACT
A reliable extraction of filament data from microscopic images is of high interest in the analysis of acto-myosin structures as early morphological markers in mechanically guided differentiation of human mesenchymal stem cells and the understanding of the underlying fiber arrangement processes. In this paper, we propose the filament sensor (FS), a fast and robust processing sequence which detects and records location, orientation, length, and width for each single filament of an image, and thus allows for the above described analysis. The extraction of these features has previously not been possible with existing methods. We evaluate the performance of the proposed FS in terms of accuracy and speed in comparison to three existing methods with respect to their limited output. Further, we provide a benchmark dataset of real cell images along with filaments manually marked by a human expert as well as simulated benchmark images. The FS clearly outperforms existing methods in terms of computational runtime and filament extraction accuracy. The implementation of the FS and the benchmark database are available as open source.

No MeSH data available.


Related in: MedlinePlus