Morphological multiscale decomposition of connected regions with emphasis on cell clusters

Schmitt, Oliver; Hasse, Maria

doi:10.1016/j.cviu.2008.08.011

Cited by 52 publications

(30 citation statements)

References 89 publications

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“…A mathematical morphology operation based multiscale decomposition method is presented in [197] for cell segmentation in bright-field microscopy images. It consists of two steps: top-down erosion and bottom-up dilation.…”

Section: Nucleus and Cell Segmentation Methodsmentioning

confidence: 99%

Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review

Xing

Yang

2016

IEEE Rev. Biomed. Eng.

443

220

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Digital pathology and microscopy image analysis is widely used for comprehensive studies of cell morphology or tissue structure. Manual assessment is labor intensive and prone to inter-observer variations. Computer-aided methods, which can significantly improve the objectivity and reproducibility, have attracted a great deal of interest in recent literatures. Among the pipeline of building a computer-aided diagnosis system, nucleus or cell detection and segmentation play a very important role to describe the molecular morphological information. In the past few decades, many efforts have been devoted to automated nucleus/cell detection and segmentation. In this review, we provide a comprehensive summary of the recent state-of-the-art nucleus/cell segmentation approaches on different types of microscopy images including bright-field, phase-contrast, differential interference contrast (DIC), fluorescence, and electron microscopies. In addition, we discuss the challenges for the current methods and the potential future work of nucleus/cell detection and segmentation.

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Section: Nucleus and Cell Segmentation Methodsmentioning

confidence: 99%

Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review

Xing

Yang

2016

IEEE Rev. Biomed. Eng.

443

220

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“…However, these methods assume that cells are isolated from each other in a dark field [21, 22]. In this paper, insect cells in images appeared as ring structures with different intensities.…”

Section: Methodsmentioning

confidence: 99%

Bright field microscopic cells counting method for BEVS using nonlinear convergence index sliding band filter

Sui¹,

Wang²,

Park³

et al. 2014

BioMed Eng OnLine

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BackgroundThe Baculovirus Expression Vector System (BEVS) is a very popular expression vector system in gene engineering. An effective host cell line cultivation protocol can facilitate the baculovirus preparation and following experiments. However, the counting of the number of host cells in the protocol is usually performed by manual observation with microscopy, which is time consuming and labor intensive work, and prone to errors for one person or between different individuals. This study aims at giving a bright field insect cells counting protocol to help improve the efficient of BEVS.MethodTo develop a reliable and accurate counting method for the host cells in the bright field, such as Sf9 insect cells, a novel method based on a nonlinear Transformed Sliding Band Filter (TSBF) was proposed. And 3 collaborators counted cells at the same time to produce the ground truth for evaluation. The performance of TSBF method was evaluated with the image datasets of Sf9 insect cells according to the different periods of cell cultivation on the cell density, error rate and growth curve.ResultsThe average error rate of our TSBF method is 2.21% on average, ranging from 0.89% to 3.97%, which exhibited an excellent performance with its high accuracy in lower error rate compared with traditional methods and manual counting. And the growth curve was much the manual method well.ConclusionResults suggest the proposed TSBF method can detect insect cells with low error rate, and it is suitable for the counting task in BEVS to take the place of manual counting by humans. Growth curve results can reflect the cells’ growth manner, which was generated by our proposed TSBF method in this paper can reflected the similar manner with it’s from the manual method. All of these proven that the proposed insect cell counting method can clearly improve the efficiency of BEVS.

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“…Various approaches have been proposed for cluster decomposition and for individual center or seed point detection. An extensive overview of related work can be found in [7]. The proposed system detects individual RBC centers using a technique based on iterative voting approach described in [6].…”

Section: Individual Cell Seed Detectionmentioning

confidence: 99%

Coupled edge profile active contours for red blood cell flow analysis

Ersoy

Bunyak

Higgins

et al. 2012

2012 9th IEEE International Symposium on Biomedical Imaging (ISBI)

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Physiological properties of blood flow at the microvasculature scale can be measured by tracking the movement and density of red blood cells (RBCs). In this paper we propose a method for individual RBC segmentation to enable tracking and capturing dynamically varying bulk transport properties. RBCs have varying annular and disk like morphologies, and are often clustered into clumps that are difficult to segment using watershed-based methods. Edge profile active contours in combination with graph coloring based coupling (C-EPAC) are introduced as a robust approach to prevent merges between adjacent, clumped RBCs by modifying the active contour energy function to be sensitive to a specific edge profile and not just the magnitude as in the traditional methods. Explicit coupling is combined with graph coloring to efficiently compute the contour evolution using the fewest number of level sets to support high-throughput studies of RBC flow characterization under varying physiological conditions.

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Morphological multiscale decomposition of connected regions with emphasis on cell clusters

Cited by 52 publications

References 89 publications

Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review

Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review

Bright field microscopic cells counting method for BEVS using nonlinear convergence index sliding band filter

Coupled edge profile active contours for red blood cell flow analysis

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