Assessment of mass detection performance in contrast enhanced digital mammography

Carton, Ann-Katherine; Carvalho, Pablo Milioni de; Li, Zhijin; Dromain, Clarisse; Muller, Serge

doi:10.1117/12.2081772

Cited by 5 publications

(8 citation statements)

References 18 publications

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“…However, simulated breast CT reconstructions showed that phantom realism was lacking, and the authors suggested that further development in modeling fibroglandular tissue structure was needed to improve realism. This phantom has been evaluated by both power‐law analysis as well as a two‐alternative forced choice (2‐AFC) psychophysical study comparing simulated and real images . To improve the realism of fibroglandular tissue structure of this phantom, Li et al .…”

Section: Digital Anthropomorphic Phantomsmentioning

confidence: 99%

“…This phantom has been evaluated by both power-law analysis as well as a two-alternative forced choice (2-AFC) psychophysical study comparing simulated and real images. 57 To improve the realism of fibroglandular tissue structure of this phantom, Li et al 58 developed a 3D breast texture model to simulate FFDM and DBT images representing the population of women seen in clinical practice. The model emulated the small-and medium-scale fibroglandular and interglandular breast tissue, and it was based on segmented clinical bCT images.…”

Section: C6 Other Digital Breast Phantomsmentioning

confidence: 99%

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Advances in digital and physical anthropomorphic breast phantoms for x‐ray imaging

Glick

Ikejimba

2018

Medical Physics

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Purpose: With the advent of three-dimensional (3D) breast imaging modalities such as digital breast tomosynthesis (DBT) and dedicated breast CT (bCT), research into new anthropomorphic breast phantoms has accelerated. These breast phantoms are important for the optimization of new breast imaging systems, assessing new regulatory submissions to prove safety and effectiveness, and for developing new approaches to acceptance and constancy testing of 3D breast imaging systems. This paper provides a review of current research investigating both digital and physical breast phantom development for use in x-ray based imaging. Methods: Two approaches for designing anthropomorphic, digital breast phantoms are discussed, procedural model-based phantom generation, where breast features are expressed using mathematical models, and patient-based generation, where breast structures from tissue specimens or patient-based breast MR or CT volumes are segmented. Following this discussion, a review of physical anthropomorphic phantoms is given, with emphasis on the advantages and disadvantages present with each approach. Conclusions: This paper provides a summary of the state-of-the-art in anthropomorphic breast phantom development for x-ray breast imaging. The primary advantage of model-based digital phantoms is that an unlimited number of phantoms with varying size, shape, and density can be generated. Current research on model-based breast phantoms is producing more and more realistic breast models; however, they probably are not yet able to pass the so-called "fool the radiologist" visualization test. Empirical patient-based breast phantoms are typically based on clinical breast CT data and look more realistic. However, clinical breast CT images have limited spatial resolution and thus do not always portray the finer details in the breast. A number of innovative solutions have been proposed for fabricating physical anthropomorphic breast phantoms based on digital phantom models; however, a number of challenges remain, including realistic modeling of x-ray attenuation properties and accurately representing high-frequency structures within breast. Published 2018. This article is a U.S. Government work and is in the public domain in the USA [https://doi.org/10.1002/mp.13110]

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Section: Digital Anthropomorphic Phantomsmentioning

confidence: 99%

Section: C6 Other Digital Breast Phantomsmentioning

confidence: 99%

Advances in digital and physical anthropomorphic breast phantoms for x‐ray imaging

Glick

Ikejimba

2018

Medical Physics

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“…Phantom image realism has been extensively assessed by statistical image properties [17], [31]- [33] and to a lesser extent by psychophysical experiments [25], [34], [35]. The more extensive reporting using statistical image properties can be attributed to the practicality of the objective measures, while psychophysical experiments involving humans are time consuming.…”

mentioning

confidence: 99%

“…In terms of psychophysical experiments, "fool-thereader" evaluations have been proposed [25], [34], [35], aiming to measure the ability of human observers to distinguish simulated phantom images from clinical images. To our knowledge, there are no publications evaluating task-driven phantom texture realism.…”

mentioning

confidence: 99%

A 3D Mathematical Breast Texture Model With Parameters Automatically Inferred From Clinical Breast CT Images

Li¹,

Carton²,

Muller³

et al. 2023

IEEE Trans. Med. Imaging

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A numerical realistic 3D anthropomorphic breast model is useful for evaluating breast imaging applications. A method is proposed to model small and medium-scale fibroglandular and intra-glandular adipose tissues observed in the center part of clinical breast CT images. The method builds upon a previously proposed model formulated as stochastic geometric processes with mathematically tractable parameters. In this work, the medium-scale parameters were automatically and objectively inferred from breast CT images. We hypothesized that a set of random ellipsoids exhibiting cluster interaction is representative to model the mediumscale intra-glandular adipose compartments. The ellipsoids were reconstructed using a multiple birth, death and shift algorithm. Then, a Matérn cluster process was used to fit the reconstructed ellipsoid centers. Finally, distributions of the ellipsoid shapes and orientations were estimated using maximum likelihood estimators. Feasibility was demonstrated on 16 volumes of interests (VOI).To assess the realism of the 3D breast texture model, β and LFE metrics computed in simulated projection images of simulated texture realizations and clinical images were compared. Visual realism was illustrated.For 12 out of 16 VOIs, our hypothesis on clustering interaction process is confirmed. The average β values from simulated texture images (3.7 to 4.2) of the 12 different VOIs are higher than the average β value from 2D clinical images (2.87). LFE of simulated texture images and clinical mammograms are similar. Compared to our previous model, whereby simulation parameters were based upon empirical observations, our inference method substantially augments the ability to generate textures with higher visual realism and larger morphological variety.

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“…Diante de tais limitações, é comum que pesquisadores criem suas próprias bases de imagens (NISHIKAWA, 1996;WARREN et al, 2007;WU et al, 2014) Diversas outras pesquisas (BERKS et al, 2010;BLIZNAKOVA et al, 2003;CARTON et al, 2015;CHEN et al, 2017;SAUNDERS et al, 2006;WARREN et al, 2013) têm sido direcionadas à elaboração de phantoms computacionais gerando imagens sintéticas.…”

Section: Cadxunclassified

Desenvolvimento de um objeto simulador de mama: investigações da percepção visual da imagem e do desempenho de esquemas CADx

Sousa¹

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Assessment of mass detection performance in contrast enhanced digital mammography

Cited by 5 publications

References 18 publications

Advances in digital and physical anthropomorphic breast phantoms for x‐ray imaging

Advances in digital and physical anthropomorphic breast phantoms for x‐ray imaging

A 3D Mathematical Breast Texture Model With Parameters Automatically Inferred From Clinical Breast CT Images

Desenvolvimento de um objeto simulador de mama: investigações da percepção visual da imagem e do desempenho de esquemas CADx

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