An Image Enhancement Algorithm Based on a Contrast Measure in the Wavelet Domain for Screening Mammograms

Tang, Jinshan; Sun, Qingling; Agyepong, Kwabena

doi:10.1109/icip.2007.4379757

Cited by 17 publications

(9 citation statements)

References 16 publications

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“…Therefore, the chosen approach, described in (11), performs the contrast enhancement at the same time that reduces noise. In (11), G is the maximum gain. From this equation, it can be noticed that pixels with probability 0 are enhanced to the maximum, while the pixels with probability 1 are eliminated.…”

Section: A Wavelet Transformmentioning

confidence: 99%

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Digital mammograms contrast enhancement using wavelets — A comparative study

Martins

Pereira

Ferreira

2014

2014 IEEE International Symposium on Medical Measurements and Applications (MeMeA)

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Mammography is the most used diagnosis method for the breast cancer. The challenge of this exam is to obtain good contrast and resolution with small radiation doses. In recent years, several efforts have been done to improve the detection efficiency of mammograms by using the potential offered by digital image processing. In this work, the potential benefits of applying the wavelet transform for microcalcifications enhancement in the digital mammograms is studied. Several contrast enhancement methods based on wavelets found in literature were adjusted and applied to a digital mammogram dataset. Their performance was evaluated by appropriate quantitative metrics, and the advantages and disadvantages of each them are described in this study. This study represents a good starting point to choose an adequate enhancement method based on wavelet transform for a specific problem.

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Section: A Wavelet Transformmentioning

confidence: 99%

“…6) Contrast : Tang et al [11] used the contrast information in the wavelet domain to perform the image contrast enhancement. The authors defined the contrast as the ratio between the detail and the approximation coefficients at the same scale, according to (19).…”

Section: A Wavelet Transformmentioning

confidence: 99%

Digital mammograms contrast enhancement using wavelets — A comparative study

Martins

Pereira

Ferreira

2014

2014 IEEE International Symposium on Medical Measurements and Applications (MeMeA)

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“…An early diagnosis is a requirement for reduction of the mortally rate from this deadly disease [1]. Modern imaging technology has created the capability of early detection of this type of cancer [2]. One of the most effective methods of early diagnosis is mammography, which allows the detection of nonpalpable, noninvasive, and early invasive tumors [1].…”

Section: Introductionmentioning

confidence: 99%

Lossless compression of mammographic images with region‐based predictor selection

Karimi

Samavi

Mahmoodzadeh

et al. 2013

IEEJ Transactions Elec Engng

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One of the main tools for early diagnosis of breast cancer is digital mammography. These images require large storage space and are difficult to be transmitted over communication links. In this paper we propose a context‐based method for lossless compression of these images. Some modifications are performed to customize the activity level classification model (ALCM) predictor to work best in mammograms. The function of the modified predictor changes for different main regions of these images. Also, best qualities of two other predictors are exploited and the results of the fittest predictor are selected adaptively for the prediction of a pixel. Moreover, context modeling is used for a better categorization of the prediction errors. The proposed algorithm was tested using images from a well‐known database and the results were compared with two standard compression methods of lossless mode of JPEG2000 and JPEG‐LS. The proposed method was proved to produce better compression results than those of the standard algorithms. © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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“…Tang Jinshan adopted a direct image contrast enhancement algorithm in the wavelet domain for screening mammograms [4]. Wang Xiu-bi [5] refers to image enhancement based on lifting wavelet transform [6]. Jinshan Tang and Qingling Sun used contrast measure in the wavelet domain for screening mammograms image enhancement algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…The different sta W io deviat n of normal  is selected by the i F function to control the scale r ge of the environme function, the parameter ian nt F with the large, middle and small scales. And the weight is basis for dramatic range and color sense[7].…”

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confidence: 99%

Industrial X-Ray Image Enhancement Algorithm based on AH and MSR

Wei¹,

Wang²,

Wang³

et al. 2011

ENG

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An X-ray image enhancement algorithm based on AH(adaptive histogram) and MSR( Multi-scale Retinex )algorithm is proposed in this paper for the industrial X-ray image, which contrast is low, and the detail features is poor. Firstly, the contrast limited adaptive histogram equalization and neighborhood algorithm is used for the image. Then the mapping is built between the image and the detail scales by the enhance function ratio rules, which is adjusted by the local contracting information. Finally, according the enhance function radios, the reconstructed image is rebuild. Compared with other image enhancement algorithms, experimental results show that our algorithm can improve the global image effectively, moreover it overcomes the visible artifacts of X-ray image. Therefore, the x-ray image becomes clearer, and a better perceptual image is acquired for the image feature recognizing and matching

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An Image Enhancement Algorithm Based on a Contrast Measure in the Wavelet Domain for Screening Mammograms

Cited by 17 publications

References 16 publications

Digital mammograms contrast enhancement using wavelets — A comparative study

Digital mammograms contrast enhancement using wavelets — A comparative study

Lossless compression of mammographic images with region‐based predictor selection

Industrial X-Ray Image Enhancement Algorithm based on AH and MSR

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An Image Enhancement Algorithm Based on a Contrast Measure in the Wavelet Domain for Screening Mammograms

Cited by 17 publications

References 16 publications

Digital mammograms contrast enhancement using wavelets &#x2014; A comparative study

Digital mammograms contrast enhancement using wavelets &#x2014; A comparative study

Lossless compression of mammographic images with region‐based predictor selection

Industrial X-Ray Image Enhancement Algorithm based on AH and MSR

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Digital mammograms contrast enhancement using wavelets — A comparative study

Digital mammograms contrast enhancement using wavelets — A comparative study