Local contrast enhancement in digital mammography by using mathematical morphology

Stojić, Tomislav; Reljin, Irini; Reljin, Branimir

doi:10.1109/isscs.2005.1511314

Cited by 26 publications

(26 citation statements)

References 3 publications

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“…For certain mammographic applications, this procedure can be iteratively repeated by using the output image of iteration as the input image for the next iteration. This gives faster results with the resulting image containing small lighter details and equalized background tissue [6].…”

Section: Morphological Filtering On a Single Scalementioning

confidence: 98%

Contrast Enhancement Techniques for Images - A Visual Analysis

Ritika¹,

Kaur²

2013

IJCA

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Section: Morphological Filtering On a Single Scalementioning

confidence: 98%

Contrast Enhancement Techniques for Images - A Visual Analysis

Ritika¹,

Kaur²

2013

IJCA

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“…Classic techniques have shown limits in medical image processing. Several enhancement approaches have been proposed in literature [64,68,69,70] aiming to improve mammographic images contrast. One of them has given better results with medical images: it is wavelet transform.…”

Section: ) Artifacts and Film Boundaries Removalmentioning

confidence: 99%

A New CAD System for Breast Microcalcifications Diagnosis

Boulehmi¹,

Mahersia²,

Hamrouni³

2016

ijacsa

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In this paper a new approach of breast microcalcifications diagnosis on digital mammograms is introduced. The proposed approach begins with a preprocessing procedure aiming artifacts and pectoral muscle removal based on morphologic operators and contrast enhancement based on galactophorous tree interpolation.The second step of the proposed CAD system consists on segmenting microcalcifications clusters, using Generalized Gaussian Density (GGD) estimation and a Bayesian backpropagation neural network.The last step is microcalcifications characterization using morphologic features which are used to feed a neuro-fuzzy system to classify the detected breast microcalcifications into benign and malignant classes.

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“…The erosion of a gray-scale digital image ( , ) by a structural element SE( , ) is defined as follows [7,9,11].…”

Section: Mathematical Morphologymentioning

confidence: 99%

“…The opening operation of image ( , ), using the structure elements SE, is defined as erosion followed by dilation and expressed as (9). Utilizing the structure element SE, the closing operation of image ( , ) is defined as dilation followed by erosion and given by (10) as follows:…”

Section: Mathematical Morphologymentioning

confidence: 99%

Feature and contrast enhancement of mammographic image based on multiscale analysis and morphology

Zhu

Yang

et al. 2013

2013 IEEE International Conference on Information and Automation (ICIA)

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A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE) and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by contrast limited adaptive histogram equalization and mathematical morphology, respectively. The enhanced image is processed by global nonlinear operator. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is measured by contrast evaluation criterion for image, signal-noise-ratio (SNR), and contrast improvement index (CII).

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Local contrast enhancement in digital mammography by using mathematical morphology

Cited by 26 publications

References 3 publications

Contrast Enhancement Techniques for Images - A Visual Analysis

Contrast Enhancement Techniques for Images - A Visual Analysis

A New CAD System for Breast Microcalcifications Diagnosis

Feature and contrast enhancement of mammographic image based on multiscale analysis and morphology

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