Half‐value layer and intensity variations as a function of position in the radiation field for film‐screen mammography

Terry, James A.; Waggener, Robert G.; Blough, Melissa M.

doi:10.1118/1.598513

Cited by 12 publications

(7 citation statements)

References 5 publications

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“…A statistically significant systematic shift of as much as 0.8 kV has been reported in one study. 20 Because the calibration curve polynomial coefficients appear to change predictably as a function of kVp, consistent kVp shifts on the order of 1 kVp could potentially be modeled as an extension of the work presented here. Likewise, because the calibration curves appear to be predictable functions of kVp changes, it may also be possible to define for a unit a correction matrix from the calibration curves presented here by making measurements at a subset of calibration points.…”

Section: Discussionmentioning

confidence: 93%

A calibration approach to glandular tissue composition estimation in digital mammography

et al. 2002

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The healthy breast is almost entirely composed of a mixture of fatty, epithelial, and stromal tissues which can be grouped into two distinctly attenuating tissue types: fatty and glandular. Further, the amount of glandular tissue is linked to breast cancer risk, so an objective quantitative analysis of glandular tissue can aid in risk estimation. Highnam and Brady have measured glandular tissue composition objectively. However, they argue that their work should only be used for "relative" tissue measurements unless a careful calibration has been performed. In this work, we perform such a "careful calibration" on a digital mammography system and use it to estimate breast tissue composition of patient breasts. We imaged 0%, 50%, and 100% glandular-equivalent phantoms of varying thicknesses for a number of clinically relevant x-ray techniques on a digital mammography system. From these images, we extracted mean signal and noise levels and computed calibration curves that can be used for quantitative tissue composition estimation. In this way, we calculate the percent glandular composition of a patient breast on a pixelwise basis. This tissue composition estimation method was applied to 23 digital mammograms. We estimated the quantitative impact of different error sources on the estimates of tissue composition. These error sources include compressed breast height estimation error, residual scattered radiation, quantum noise, and beam hardening. Errors in the compressed breast height estimate contribute the most error in tissue composition--on the order of +/-7% for a 4 cm compressed breast height: The spatially varying scattered radiation will contribute quantitatively less error overall, but may be significant in regions near the skinline. It is calculated that for a 4 cm compressed breast height, a residual scatter signal error is mitigated by approximately sixfold in the composition estimate. The error in composition due to the quantum noise, which is the limiting noise source in the system, is shown to be less than 1% glandular for most breasts.

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Section: Discussionmentioning

confidence: 93%

A calibration approach to glandular tissue composition estimation in digital mammography

et al. 2002

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“…Several effects contribute to radiation field nonuniformities: the heel effect along the anode-cathode axis, the inverse square law, and differential photon-path lengths through various attenuating media ͑the Be window of the x-ray tube, the added filtration, the mirror, and the compression paddle͒. 17 The angle of incidence in detector elements may also play a role. The most apparent nonuniformity is the heel effect along the anode-cathode axis.…”

Section: Flat-field Inhomogeneitiesmentioning

confidence: 99%

Validation of MTF measurement for digital mammography quality control

et al. 2005

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The modulation transfer function (MTF) describes the spatial resolution properties of imaging systems. In this work, the accuracy of our implementation of the edge method for calculating the presampled MTF was examined. Synthetic edge images with known MTF were used as gold standards for determining the robustness of the edge method. These images simulated realistic data from clinical digital mammography systems, and contained intrinsic system factors that could affect the MTF accuracy, such as noise, scatter, and flat-field nonuniformities. Our algorithm is not influenced by detector dose variations for MTF accuracy up to 1/2 the sampling frequency. We investigated several methods for noise reduction, including truncating the supersampled line spread function (LSF), windowing the LSF, applying a local exponential fit to the LSF, and applying a monotonic constraint to the supersampled edge spread function. Only the monotonic constraint did not introduce a systematic error; the other methods could result in MTF underestimation. Overall, our edge method consistently computed MTFs which were in good agreement with the true MTF. The edge method was then applied to images from a commercial storage-phosphor based digital mammography system. The calculated MTF was affected by the size (sides of 2.5, 5, or 10 cm) and the composition (lead or tungsten) of the edge device. However, the effects on the MTF were observed only with regard to the low frequency drop (LFD). Scatter nonuniformity was dependent on edge size, and could lead to slight underestimation of LFD. Nevertheless, this negative effect could be minimized by using an edge of 5 cm or larger. An edge composed of lead is susceptible to L-fluorescence, which causes overestimation of the LFD. The results of this work are intended to underline the need for clear guidelines if the MTF is to be given a more crucial role in acceptance tests and routine assessment of digital mammography systems: the MTF algorithm and edge object test tool need to be publicly validated.

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“…The combined result of all of the effects described above is that both the intensity and the energy spectrum of x rays vary along the imaging plane. [5][6][7]…”

Section: Theorymentioning

confidence: 99%

Field nonuniformity correction for quantitative analysis of digitized mammograms

Pawluczyk

Yaffe

2001

Medical Physics

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Several factors, including the heel effect, variation in distance from the x-ray source to points in the image and path obliquity contribute to the signal nonuniformity of mammograms. To best use digitized mammograms for quantitative image analysis, these field non-uniformities must be corrected. An empirically based correction method, which uses a bowl-shaped calibration phantom, has been developed. Due to the annular spherical shape of the phantom, its attenuation is constant over the entire image. Remaining nonuniformities are due only to the heel and inverse square effects as well as the variable path through the beam filter, compression plate and image receptor. In logarithmic space, a normalized image of the phantom can be added to mammograms to correct for these effects. Then, an analytical correction for path obliquity in the breast can be applied to the images. It was found that the correction causes the errors associated with field nonuniformity to be reduced from 14% to 2% for a 4 cm block of material corresponding to a combination of 50% fibroglandular and 50% fatty breast tissue. A repeatability study has been conducted to show that in regions as far as 20 cm away from the chest wall, variations due to imaging conditions and phantom alignment contribute to<2% of overall corrected signal.

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Half‐value layer and intensity variations as a function of position in the radiation field for film‐screen mammography

Cited by 12 publications

References 5 publications

A calibration approach to glandular tissue composition estimation in digital mammography

A calibration approach to glandular tissue composition estimation in digital mammography

Validation of MTF measurement for digital mammography quality control

Field nonuniformity correction for quantitative analysis of digitized mammograms

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