Application of morphological transformations to the analysis of two-dimensional electrophoretic gels of biological materials

Skolnick, M.

doi:10.1016/0734-189x(86)90003-4

Cited by 64 publications

(27 citation statements)

References 9 publications

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“…A regional minimum is at the heart of a watershed, as water will converge toward it from its surroundings and will stay trapped there. In addition to their key role in the watershed concept, regional minima have also been related to the location of significant features, such as blobs in electrophoretic gels [19]. An interesting property of regional minima is that they cannot touch one another, as they must be at least one pixel apart.…”

Section: Global Local and Regional Minimamentioning

confidence: 99%

Watershed-Based Segmentation and Region Merging

Bleau¹,

Leon²

2000

Computer Vision and Image Understanding

269

116

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Section: Global Local and Regional Minimamentioning

confidence: 99%

Watershed-Based Segmentation and Region Merging

Bleau¹,

Leon²

2000

Computer Vision and Image Understanding

269

116

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“…Image morphology is performed by successively dilating and eroding images with structural elements similar to the features in the image one wants to keep or remove. The use of morphology in 2-DE and for images in general is well described by Skolnick [11] and Sternberg [12]. The selected structural element for streak identification is a line 61 pixels in length, and for protein spot regions a circle with a diameter of 40 pixels is chosen.…”

Section: Identification Of Spot Regionsmentioning

confidence: 99%

An improved pixel‐based approach for analyzing images in two‐dimensional gel electrophoresis

Rye

Færgestad²,

Martens

et al. 2008

Electrophoresis

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An improved pixel-based approach for analyzing 2-DE images is presented. The key feature of the method is to create a mask based on all gels in the experiment using image morphology, followed by multivariate analysis on the pixel level. The method reduces the impact of noise and background by identifying regions in the image where protein spots are present, but make no assumption on individual spot boundaries for isolated spots. This makes it possible to detect significant changes in complex regions, and visualize these changes over multiple gels in an easy way. False missing values and spot volumes caused by imposing erroneous spot boundaries are thus circumvented. The approach presented gives improved pixel-based information from the gels, and is also an alternative to existing methods for data-reduction, significance testing and visualization of 2-DE data. Results are compared with software using a common spot boundary approach on an experiment consisting of 35 full size gel images. Gel alignment is required before analysis.

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“…Q. E. D. Equations (14), (15) and (16), (17) imply that there is a duality with respect to set complementation between set erosion and dilation-as well as between set opening and closing. Likewise, there is a duality with respect to function negation between the corresponding FP filters.…”

Section: E Properties Of Morphological Filtersmentioning

confidence: 99%

“…They stem from the basic operations of a set-theoretical method for image analysis, called mathematical morphology, which was introduced by Matheron [l] and Serra [2]. In this method, each signal is viewed as a set in a Euclidean space, and the morphological filters are set operations that transform the graph of the signal Manuscript received May 19, 1986 [15]; automated industrial inspection [16], [17]; shape recognition [18]; nonlinear filtering [19], [20] [20], [13]; thinning [2], [5], [21]- [22]; enhancement [2], [21]; representation and coding [20], [22]; texture analysis [23]; and shape smoothing 121, [20], [22], [24]. Currently, there are several commercialized image analyzers or other pipelined or parallel computer architectures [25]- [28] that use morphological filters (mainly for binary signals) among their main operations to extract pictorial information.…”

Section: I Introductionmentioning

confidence: 99%

Morphological filters--Part I: Their set-theoretic analysis and relations to linear shift-invariant filters

Maragos

Schafer

1987

IEEE Trans. Acoust., Speech, Signal Process.

614

209

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Abstract-This paper examines the set-theoretic interpretation of morphological filters in the framework of mathematical morphology and introduces the representation of classical linear filters in terms of morphological correlations, which involve supremumlinfimum operations and additions. Binary signals are classified as sets, and multilevel signals as functions. Two set-theoretic representations of signals are reviewed. Filters are classified as set-processing (SP) or function-processing (FP). Conditions are provided for certain FP filters that pass binary signals to commute with signal thresholding because then they can be analyzed and implemented as SP filters.The basic morphological operations of set erosion, dilation, opening, and closing are related to Minkowski set operations and are used to construct FP morphological filters. Emphasis is then given to analytically and geometrically quantifying the similarities and differences between morphological filtering of signals by sets and functions; the latter case allows the definition of morphological convolutions and correlations. Toward this goal, various properties of FP morphological filters are also examined.Linear shift-invariant filters (due to their translation-invariance) are uniquely characterized by their kernel, which is a special collection of input signals. Increasing linear filters are represented as the supremum of erosions by their kernel functions. If the filters are also discrete and have a finite-extent impulse response, they can be represented as the supremum of erosions only by their minimal (with respect to a signal ordering) kernel functions. Stable linear filters can be represented as the sum of (at most) two weighted suprema of erosions. These results demonstrate the power of mathematical morphology as a unifying approach to both linear and nonlinear signal-shaping strategies.M

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Application of morphological transformations to the analysis of two-dimensional electrophoretic gels of biological materials

Cited by 64 publications

References 9 publications

Watershed-Based Segmentation and Region Merging

Watershed-Based Segmentation and Region Merging

An improved pixel‐based approach for analyzing images in two‐dimensional gel electrophoresis

Morphological filters--Part I: Their set-theoretic analysis and relations to linear shift-invariant filters

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