Characterization of scatter in digital mammography from physical measurements

Leon, Stephanie; Brateman, Libby; Wagner, Louis K.

doi:10.1118/1.4873321

Cited by 7 publications

(11 citation statements)

References 21 publications

(22 reference statements)

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“…1 They also suggest that breast glandularity does not present a problem for application of the data to a scatter-correction image processing program.…”

Section: Discussionmentioning

confidence: 98%

“…1) in Tables II and III, without a grid, and Tables IV and V, with a grid. In addition to the data presented in these tables, simulations were also performed using clinically appropriate techniques, as described in Sec.…”

Section: A Sfmentioning

confidence: 96%

“…1 The accuracy of the scatter-correction process depends strongly on the accuracy of the modeled scatter; an inaccurate correction would result in a suboptimal improvement, or even a degradation, of the mammographic image quality. Thus, it is important to have a high level of confidence regarding the accuracy of the data set.…”

Section: Introductionmentioning

confidence: 99%

“…2 In this model, the scatter kernel is the response function to a perfect impulse of particles [Eq. (1)], where h D (r) represents the PSF, r represents the distance from the origin, k represents the mean lateral propagation distance of the scatter (the mean radial extent or MRE), ρ represents the scatter fraction (SF), and the Dirac delta function indicates the portion of radiation that is directly mapped…”

Section: Introductionmentioning

confidence: 99%

“…The impact of scattered radiation on image quality, and the potential benefits of the development of an image processingbased method of scatter correction, have been described previously. 1 The accuracy of the scatter-correction process depends strongly on the accuracy of the modeled scatter; an inaccurate correction would result in a suboptimal improvement, or even a degradation, of the mammographic image quality. Thus, it is important to have a high level of confidence regarding the accuracy of the data set.…”

Section: Introductionmentioning

confidence: 99%

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Characterization of scatter in digital mammography from use of Monte Carlo simulations and comparison to physical measurements

Leon¹,

Brateman

Wagner³

2014

Medical Physics

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The findings show agreement between the physical measurements published previously and the Monte Carlo simulations presented here; the resulting data can therefore be used more confidently for an application such as image processing-based scatter correction. The findings also suggest that breast composition does not have a major impact on the scatter characteristics of breast tissue. Application of the scatter data to the development of a scatter-correction software program can be simplified by ignoring the variations in density among breast tissues.

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“…1 They also suggest that breast glandularity does not present a problem for application of the data to a scatter-correction image processing program.…”

Section: Discussionmentioning

confidence: 98%

Section: A Sfmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Characterization of scatter in digital mammography from use of Monte Carlo simulations and comparison to physical measurements

Leon¹,

Brateman

Wagner³

2014

Medical Physics

Self Cite

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Quantitative evaluation of breast density using a dual‐energy technique on a digital breast tomosynthesis system

Lu¹,

Yeh

Cao

et al. 2019

J Applied Clin Med Phys

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Purpose Although breast density is considered a strong risk factor of breast cancer, its quantitative assessment is difficult. To investigate a quantitative method of measuring breast density using dual‐energy mammographic imaging with central digital breast tomosynthesis in physically uniform and nonuniform phantoms. Material and methods The dual‐energy imaging unit used a tungsten anode and silver filter with 30 kVp for high‐energy images and 20 kVp for low‐energy images. Uniform glandular‐equivalent phantoms were used to calibrate a dual‐energy based decomposition algorithm. The first study used uniform breast phantoms which ranged in thicknesses from 20 to 70 mm, in 10‐mm increments, and which provided 30%, 50%, and 70% of breast density. The second study used uniform phantoms ranging from 10% to 90% of breast density. The third study used non‐uniform phantoms (at an average density of 50%) with a thickness which ranged from 20 to 90 mm, in 10‐mm increments. Results The root mean square error of breast density measurements was 2.64–3.34% for the uniform, variable thickness phantoms, 4.17% for the uniform, variable density phantoms, and 4.49% for the nonuniform, variable thickness phantoms. Conclusion The dual‐energy technique could be used to measure breast density with a margin of error of < 10% using digital breast tomosynthesis.

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A general framework for the assessment of scatter correction techniques in digital mammography

Angelone,

Ponsiglione,

Grassi

et al. 2024

Biomedical Signal Processing and Control

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Characterization of scatter in digital mammography from physical measurements

Cited by 7 publications

References 21 publications

Characterization of scatter in digital mammography from use of Monte Carlo simulations and comparison to physical measurements

Characterization of scatter in digital mammography from use of Monte Carlo simulations and comparison to physical measurements

Quantitative evaluation of breast density using a dual‐energy technique on a digital breast tomosynthesis system

A general framework for the assessment of scatter correction techniques in digital mammography

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