Fractal dimension analysis and mathematical morphology of structural changes in actin filaments imaged by electron microscopy

Kimori, Yoshitaka; Katayama, Eisaku; Morone, Nobuhiro; Kodama, Takao

doi:10.1016/j.jsb.2011.07.007

Cited by 15 publications

(12 citation statements)

References 40 publications

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“…To overcome this limitation, a type of extended mathematical morphology called RMP has been proposed [23-25]. RMP rotates the original image with respect to the structuring element that is fixed in one direction.…”

Section: Methodsmentioning

confidence: 99%

“…This study describes an approach to medical image processing using a type of mathematical morphology called rotational morphological processing (RMP) [23-25] for enhancement of mass lesions in medical images captured by various modalities. The proposed method involves two consecutive steps: (1) selective extraction of target features by mathematical morphology and (2) enhancement of the extracted features by two contrast modification techniques.…”

Section: Introductionmentioning

confidence: 99%

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Mathematical morphology-based approach to the enhancement of morphological features in medical images

Kimori

2011

J Clin Bioinformatics

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BackgroundMedical image processing is essential in many fields of medical research and clinical practice because it greatly facilitates early and accurate detection and diagnosis of diseases. In particular, contrast enhancement is important for optimal image quality and visibility. This paper proposes a new image processing method for enhancing morphological features of masses and other abnormalities in medical images.MethodThe proposed method involves two steps: (1) selective extraction of target features by mathematical morphology and (2) enhancement of the extracted features by two contrast modification techniques.ResultsThe goal of the proposed method is to enable enhancement of fine morphological features of a lesion region with high suppression of surrounding tissues. The effectiveness of the method was evaluated in quantitative terms of the contrast improvement ratio. The results clearly show that the method outperforms five conventional contrast enhancement methods. The effectiveness and usefulness of the proposed method were further demonstrated by application to three types of medical images: a mammographic image, a chest radiographic image, and a retinal image.ConclusionThe proposed method enables specific extraction and enhancement of mass lesions, which is essential for clinical diagnosis based on medical image analysis. Thus, the method can be expected to achieve automatic recognition of lesion location and quantitative analysis of legion morphology.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mathematical morphology-based approach to the enhancement of morphological features in medical images

Kimori

2011

J Clin Bioinformatics

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“…evolution studies of nanoscale TiO 2 in aquatic media (Chowdhury et al, 2013;Godinez and Darnault, 2011;Loosli et al, 2013;Xu et al, 2014), studies of fullerite nanoparticles in electrolyte solutions (Meng et al, 2013). Fractal image analysis methods were used to classify organic and inorganic structures (Kimori et al, 2011;Kong et al, 2014;Papanicolaou et al, 2012;Smith et al, 1996, Neil andCurtis, 1997). Neil et al (2016) studied fractal structures of iron oxide nanoparticles aggregated with natural organic matter and arsenate to better predict the sedimentation rates in the environment.…”

Section: Fm Applied To Aggregation Modellingmentioning

confidence: 99%

“…The Polar IFS and the Generic Programming image-decoding methods are capable of solving the task of defining an IFS for a given image (Collet et al, 2000;Hart, 1996;Hart et al, 1997). An electron microscopy image of an aggregate can also be reduced to its outlines to simplify the analysis (Kimori et al, 2011;Du et al, 2012;Ferreiro et al, 2013;Hagerhall et al, 2004). The symmetry types can be extracted from new geometrical theories developed for new tasks in material engineering (Lord et al, 2006;Shevchenko and Mackay, 2011;Ivanov and Talanov, 2013;Bokeloh et al, 2010).…”

Section: Step 1 Collecting Empirical Data and Building The Fractal Mmentioning

confidence: 99%

Improving the prediction of environmental fate of engineered nanomaterials by fractal modelling

Avilov

Lamon

Hristozov

et al. 2017

Environment International

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A critical analysis of the available engineered nanomaterials (ENMs) environmental fate modelling approaches indicates that existing tools do not satisfactorily account for the complexities of nanoscale phenomena. Fractal modelling (FM) can complement existing kinetic fate models by including more accurate interpretations of shape and structure, density and collision efficiency parameters to better describe homo- and heteroaggregation. Pathways to including hierarchical symmetry concepts and a route to establishing a structural classification of nanomaterials based on FM are proposed.

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“…Commonly the structural elements which have same shape and size are called simple structural element, and elements which have different shape and size are called multi-scale and multi-form elements [15,16] . In the process of image, if only the single structural element is used, then the processed image has only one sort of geometrical information, it goes against the maintenance of image details.…”

Section: Basic Ideamentioning

confidence: 99%

Application of mathematical morphology in surface detection of infrared image for plume

Qiang

Liu

et al. 2013

SPIE Proceedings

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This paper presents a method for surface detection of Infrared Image for plume. First of all, the binarization of Infrared Image is achieved by Min-Max Method, then edge detection operator is constructed based on Multi-scale and Multi-form morphological structural element of mathematical morphology, to detect the edge of Engine's plume of Infrared Image. Results showed that our method has better capability in depressing the noise interference comparatively to the traditional edge detection operator, and meet the real-time requirement.

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Fractal dimension analysis and mathematical morphology of structural changes in actin filaments imaged by electron microscopy

Cited by 15 publications

References 40 publications

Mathematical morphology-based approach to the enhancement of morphological features in medical images

Mathematical morphology-based approach to the enhancement of morphological features in medical images

Improving the prediction of environmental fate of engineered nanomaterials by fractal modelling

Application of mathematical morphology in surface detection of infrared image for plume

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