A Simple Algorithm of Superpixel Segmentation with Boundary Constraint

Zhang, Yongxia; Li, Xuemei; Gao, Xifeng; Zhang, Caiming

doi:10.1109/tcsvt.2016.2539839

Cited by 48 publications

(47 citation statements)

References 32 publications

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“…In the first module, 2D fluorescence images are loaded as a stack, and the user selects ROIs using a polygon tool; multiple ROIs can be selected for each loaded image. A segmentation process is implemented which divides each ROI into smaller segments using either a moving square algorithm or a simple linear iterative clustering algorithm (SLIC) (for more details see Supplementary Note 3) [44][45][46] . The pixel locations for each segment are saved and paired with the corresponding source image.…”

Section: Methodsmentioning

confidence: 99%

A general method to quantify ligand-driven oligomerization using single- or two-photon excitation microscopy

Biener

Ward

et al. 2018

Preprint

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Current technologies for probing membrane protein association and stability in cells are either very laborious or lack the bandwidth needed for fully quantitative analysis. Here we introduce a platform, termed one-or two-dimensional fluorescence intensity fluctuation spectrometry, for determining the identity, abundance, and stability of oligomers of differing sizes. The sensitivity of this approach is demonstrated by using monomers and oligomers of known sizes in both solutions and cell membranes. The analysis was extended to uncover the oligomeric states and their stability for both the epidermal growth factor receptor, a receptor tyrosine kinase, and the G protein-coupled secretin receptor. In both cases, agonist ligand binding shifted the equilibrium from monomers or dimers to rather large oligomers. Our method can be used in conjunction with a variety of light-based microscopy techniques, is several orders of magnitude faster than current approaches, and is scalable for high-throughput analyses.

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Section: Methodsmentioning

confidence: 99%

A general method to quantify ligand-driven oligomerization using single- or two-photon excitation microscopy

Biener

Ward

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…In Machairas et al (2015), the image gradient information is used to constrain the superpixel boundaries, but the results on superpixel evaluation metrics are lower than the ones of SLIC (Achanta et al, 2012). In Zhang et al (2016), the local gradient information is considered to improve the superpixel boundaries evolution. However, the computational cost of the method is increased by a 10× order of magnitude compared to SLIC.…”

Section: Contour Constraintmentioning

confidence: 99%

Robust superpixels using color and contour features along linear path

Giraud

Papadakis

2018

Computer Vision and Image Understanding

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“…32, the circularity metric was introduced to locally evaluate the compactness of the superpixels. This measure is the usual local regularity metric, and has been considered in state-ofthe-art works, 11,16,30,40 and benchmarks. 34,37,41 This circularity C is defined for a superpixel shape S as follows:…”

Section: Regularitymentioning

confidence: 99%

Evaluation framework of superpixel methods with a global regularity measure

Giraud

Papadakis

2017

J. Electron. Imaging

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In the superpixel literature, the comparison of state-of-the-art methods can be biased by the non-robustness of some metrics to decomposition aspects, such as the superpixel scale. Moreover, most recent decomposition methods allow to set a shape regularity parameter, which can have a substantial impact on the measured performances. In this paper, we introduce an evaluation framework, that aims to unify the comparison process of superpixel methods. We investigate the limitations of existing metrics, and propose to evaluate each of the three core decomposition aspects: color homogeneity, respect of image objects and shape regularity. To measure the regularity aspect, we propose a new global regularity measure (GR), which addresses the non-robustness of state-of-the-art metrics. We evaluate recent superpixel methods with these criteria, at several superpixel scales and regularity levels. The proposed framework reduces the bias in the comparison process of state-of-the-art superpixel methods. Finally, we demonstrate that the proposed GR measure is correlated with the performances of various applications.

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A Simple Algorithm of Superpixel Segmentation with Boundary Constraint

Cited by 48 publications

References 32 publications

A general method to quantify ligand-driven oligomerization using single- or two-photon excitation microscopy

A general method to quantify ligand-driven oligomerization using single- or two-photon excitation microscopy

Robust superpixels using color and contour features along linear path

Evaluation framework of superpixel methods with a global regularity measure

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