Computer aided detection of masses in digital breast tomosynthesis: A review

Caroline, B. Elizabeth; Vaijayanthi, N.

doi:10.1109/incoset.2012.6513903

Cited by 1 publication

(5 citation statements)

References 17 publications

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“…Fig. 2 illustrates the recent techniques on 3D-MMG [14], [15]. Digital x-ray tomosynthesis is a technique that uses slice images from basic x-ray to create a 3D picture.…”

Section: Relevant Methodsmentioning

confidence: 99%

“…\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$I_{0}$ \end{document} is the original intensity and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$I_{tomo}$ \end{document} is the intensity exiting the tissue. The slice of 3D structure must be processed in order to compile all images from reduced view angles in tomosynthesis [14], [15].…”

Section: Relevant Methodsmentioning

confidence: 99%

“…The slices from tomosynthesis are digitally combined using iterative reconstruction techniques [14]. Iterative reconstruction is a means to create a 3D object from the 2D images.…”

Section: Relevant Methodsmentioning

confidence: 99%

“…l, m, n are used to represent the dimensions in a 3D space. The number of images taken must be 2K+1 [14].…”

Section: Relevant Methodsmentioning

confidence: 99%

“…3-dimensional mammogram (3D-MMG), also called tomosynthesis, started developing in the last 5 years as a common screening procedure [14]. Elastography, however, has not been used for 3D-MMG.…”

Section: Introductionmentioning

confidence: 99%

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Elastographic Tomosynthesis From X-Ray Strain Imaging of Breast Cancer

Sutphin

Olson

Motai

et al. 2019

IEEE J. Transl. Eng. Health Med.

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Noncancerous breast tissue and cancerous breast tissue have different elastic properties. In particular, cancerous breast tumors are stiff when compared to the noncancerous surrounding tissue. This difference in elasticity can be used as a means for detection through the method of elastographic tomosynthesis by means of physical modulation. This paper deals with a method to visualize elasticity of soft tissues, particularly breast tissues, via x-ray tomosynthesis. X-ray tomosynthesis is now used to visualize breast tissues with better resolution than the conventional single-shot mammography. The advantage of X-ray tomosynthesis over X-ray CT is that fewer projections are needed than CT to perform the reconstruction, thus radiation exposure and cost are both reduced. Two phantoms were used for the testing of this method, a physical phantom and an in silico phantom. The standard root mean square error in the tomosynthesis for the physical phantom was 2.093 and the error in the in silico phantom was negligible. The elastographs were created through the use of displacement and strain graphing. A Gaussian Mixture Model with an expectation–maximization clustering algorithm was applied in three dimensions with an error of 16.667%. The results of this paper have been substantial when using phantom data. There are no equivalent comparisons yet in 3D x-ray elastographic tomosynthesis. Tomosynthesis with and without physical modulation in the 3D elastograph can identify feature groupings used for biopsy. The studies have potential to be applied to human test data used as a guide for biopsy to improve accuracy of diagnosis results. Further research on this topic could prove to yield new techniques for human patient diagnosis purposes.

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“…Fig. 2 illustrates the recent techniques on 3D-MMG [14], [15]. Digital x-ray tomosynthesis is a technique that uses slice images from basic x-ray to create a 3D picture.…”

Section: Relevant Methodsmentioning

confidence: 99%

Section: Relevant Methodsmentioning

confidence: 99%

“…The slices from tomosynthesis are digitally combined using iterative reconstruction techniques [14]. Iterative reconstruction is a means to create a 3D object from the 2D images.…”

Section: Relevant Methodsmentioning

confidence: 99%

“…l, m, n are used to represent the dimensions in a 3D space. The number of images taken must be 2K+1 [14].…”

Section: Relevant Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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