A digital density equalization technique to improve visualization of breast periphery in mammography.

Stefanoyiannis, A.P.; Costaridou, Lena; Sakellaropoulos, P.; Panayiotakis, G.

doi:10.1259/bjr.73.868.10844867

Cited by 17 publications

(13 citation statements)

References 27 publications

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“…Several methods have been proposed for overexposed area correction in mammography, which can be classified into non-parametric [14][15][16] or parametric [17][18][19][20][21] approaches. The former ones try to adjust the intensity of overexposed areas by means of traditional image processing techniques, like segmentation and equalisation.…”

Section: Introductionmentioning

confidence: 99%

“…The former ones try to adjust the intensity of overexposed areas by means of traditional image processing techniques, like segmentation and equalisation. On the other hand, parametric approaches adjust the intensity of the images according to a given model, which may be as specific as the type of digital detector [17] or as general as a 3D representation of the breast [18][19][20][21]. A different approach was proposed by Goodsitt et al [22,23] who designed physical filters to adjust x-ray beam distribution in order to compensate the tissue thickness.…”

Section: Introductionmentioning

confidence: 99%

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Breast peripheral area correction in digital mammograms

Tortajada

Oliver

Martí

et al. 2014

Computers in Biology and Medicine

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Digital mammograms may present an overexposed area in the peripheral part of the breast, which is visually shown as a darker area with lower contrast. This has a direct impact on image quality and affects image visualisation and assessment. This paper presents an automatic method to enhance the overexposed peripheral breast area providing a more homogeneous and improved view of the whole mammogram. The method automatically restores the overexposed area by equalising the image using information from the intensity of non-overexposed neighbour pixels. The correction is based on a multiplicative model and on the computation of the distance map from the breast boundary. A total of 334 digital mammograms were used for evaluation. Mammograms before and after enhancement were evaluated by an expert using visual comparison. In 90.42% of the cases, the enhancement obtained improved visualisation compared to the original image in terms of contrast and detail. Moreover, results show that lesions found in the peripheral area after enhancement presented a more homogeneous intensity distribution. Hence, peripheral enhancement is shown to improve visualisation and will play a role in further development of CAD systems in mammography.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Breast peripheral area correction in digital mammograms

Tortajada

Oliver

Martí

et al. 2014

Computers in Biology and Medicine

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“…Postprocessing solutions have also been attempted to overcome the limitations of film. 6 The inexorably coupled acquisition and display and the dynamic range limitations of film are not present in digital mammography. Once images are acquired using digital technology, those images may be arbitrarily windowed, leveled, or otherwise processed for more adequate display on either softcopy ͑monitors͒ or hardcopy ͑film͒ devices.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of detector dynamic range in the x-ray exposure domain in mammography: A comparison between film-screen and flat panel detector systems

et al. 2003

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Digital detectors in mammography have wide dynamic range in addition to the benefit of decoupled acquisition and display. How wide the dynamic range is and how it compares to film-screen systems in the clinical x-ray exposure domain are unclear. In this work, we compare the effective dynamic ranges of film-screen and flat panel mammography systems, along with the dynamic ranges of their component image receptors in the clinical x-ray exposure domain. An ACR mammography phantom was imaged using variable mAs (exposure) values for both systems. The dynamic range of the contrast-limited film-screen system was defined as that ratio of mAs (exposure) values for a 26 kVp Mo/Mo (HVL=0.34 mm Al) beam that yielded passing phantom scores. The same approach was done for the noise-limited digital system. Data from three independent observers delineated a useful phantom background optical density range of 1.27 to 2.63, which corresponded to a dynamic range of 2.3 +/- 0.53. The digital system had a dynamic range of 9.9 +/- 1.8, which was wider than the film-screen system (p<0.02). The dynamic range of the film-screen system was limited by the dynamic range of the film. The digital detector, on the other hand, had an estimated dynamic range of 42, which was wider than the dynamic range of the digital system in its entirety by a factor of 4. The generator/tube combination was the limiting factor in determining the digital system's dynamic range.

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“…A second limitation is the use of the anatomical filter to obtain exposure equalisation at the breast periphery, which limits the application of the technique to CC views. Further work should be carried out in the field of digital density equalisation techniques (HIGHNAM et al, 1997;STEFANOYIANNIS et al, 2000;VELDKAMP and KARSSEMEIJER, 2000), which allow application of the technique to both CC and mediolateral (ML) views.…”

Section: Resultsmentioning

confidence: 99%

“…Exposure equalisation can be performed using either anatomical filters (LAM and CHAN, 1990;PANAYIOTAKIS et el., 1992) or more sophisticated techniques that modulate the entrance exposure, based on feed-back of the regional variations in X-ray attenuation (OESTMANN et al, 1994;SABOL and PLEWES, 1996). The existing methods for density equalisation mainly employ computer-based procedures for the matching of the optical density between the periphery and the central part of the breast (BICK et al, 1996;BYNG et al, 1997;HIGHNAM et al, 1997;STEFANOYIANNIS et al, 2000;VELDKAMP and KARSSEMEIJER, 2000).…”

Section: Image Acquisitionmentioning

confidence: 99%

Model-based technique for the measurement of skin thickness in mammography

et al. 2002

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A model-based method is proposed for the measurement of breast skin thickness from digitised mammograms that takes into account both the geometric and radiographic properties of the skin region. The method initially identifies a salient feature that discriminates the skin from the other anatomical structures of the breast. Its identification is based on a multi-scale grey-level gradient estimation, using a wavelet decomposition of the image. The spatial distribution of this feature is organised as a graph, with each of its nodes associated with a binary set of interpretation labels. A Markov random field is defined on the set of labels, and the best graph labelling is finally determined with a maximum a posteriori (MAP) probability criterion. The method was applied on 11 mammograms with improved contrast characteristics at the breast periphery, obtained by an exposure equalisation technique during image acquisition. The validation of the approach was performed by calculating the root mean square (RMS) error between the detected skin thickness and manual measurements performed on each of the films. The resulting error values ranged from 0.1 mm to 0.2 mm for normal cases and reached a maximum of 0.5mm in pathological cases with advanced skin thickening.

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A digital density equalization technique to improve visualization of breast periphery in mammography.

Cited by 17 publications

References 27 publications

Breast peripheral area correction in digital mammograms

Breast peripheral area correction in digital mammograms

Evaluation of detector dynamic range in the x-ray exposure domain in mammography: A comparison between film-screen and flat panel detector systems

Model-based technique for the measurement of skin thickness in mammography

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