Literature DB >> 2315379

Characterisation of mammographic parenchymal pattern by fractal dimension.

C B Caldwell1, S J Stapleton, D W Holdsworth, R A Jong, W J Weiser, G Cooke, M J Yaffe.   

Abstract

A consistent, quantitative, observer-independent method of characterising mammographic parenchymal pattern is described. The method is based on the calculation of the 'fractal dimension' of digitised mammograms. The degree of correlation between the parenchymal pattern classifications by a fractal-based system and those of radiologists is assessed. For a set of 70 mammograms, average weighted proportion agreement among three radiologists in calling Wolfe grades was 85%, while agreement between the radiologists and our fractal classifier was 84%. The method developed may prove to be useful in establishing an index of risk for breast cancer and, ultimately, in determining intervals between examinations for individuals in a mammographic screening programme.

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Year:  1990        PMID: 2315379     DOI: 10.1088/0031-9155/35/2/004

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  30 in total

1.  Evaluation of an improved algorithm for producing realistic 3D breast software phantoms: application for mammography.

Authors:  K Bliznakova; S Suryanarayanan; A Karellas; N Pallikarakis
Journal:  Med Phys       Date:  2010-11       Impact factor: 4.071

2.  Parenchymal texture analysis in digital mammography: robust texture feature identification and equivalence across devices.

Authors:  Brad M Keller; Andrew Oustimov; Yan Wang; Jinbo Chen; Raymond J Acciavatti; Yuanjie Zheng; Shonket Ray; James C Gee; Andrew D A Maidment; Despina Kontos
Journal:  J Med Imaging (Bellingham)       Date:  2015-04-03

3.  A computer-simulated liver phantom (virtual liver phantom) for multidetector computed tomography evaluation.

Authors:  Yoshinori Funama; Kazuo Awai; Osamu Miyazaki; Yoshiharu Nakayama; Da Liu; Taiga Goto; Yasuyuki Yamashita; Shinichi Hori
Journal:  Eur Radiol       Date:  2005-10-20       Impact factor: 5.315

4.  Fractal analysis of contours of breast masses in mammograms.

Authors:  Rangaraj M Rangayyan; Thanh M Nguyen
Journal:  J Digit Imaging       Date:  2007-09       Impact factor: 4.056

5.  Characterization and classification of tumor lesions using computerized fractal-based texture analysis and support vector machines in digital mammograms.

Authors:  Qi Guo; Jiaqing Shao; Virginie F Ruiz
Journal:  Int J Comput Assist Radiol Surg       Date:  2008-10-28       Impact factor: 2.924

6.  Methodology for generating a 3D computerized breast phantom from empirical data.

Authors:  Christina M Li; W Paul Segars; Georgia D Tourassi; John M Boone; James T Dobbins
Journal:  Med Phys       Date:  2009-07       Impact factor: 4.071

7.  A breast density index for digital mammograms based on radiologists' ranking.

Authors:  J M Boone; K K Lindfors; C S Beatty; J A Seibert
Journal:  J Digit Imaging       Date:  1998-08       Impact factor: 4.056

8.  Characterisation of structural changes in the arterial elastic matrix by a new fractal feature: directional fractal curve.

Authors:  C F Jiang; A P Avolio
Journal:  Med Biol Eng Comput       Date:  1997-05       Impact factor: 2.602

9.  Using Convolutional Neural Networks for Enhanced Capture of Breast Parenchymal Complexity Patterns Associated with Breast Cancer Risk.

Authors:  Aimilia Gastounioti; Andrew Oustimov; Meng-Kang Hsieh; Lauren Pantalone; Emily F Conant; Despina Kontos
Journal:  Acad Radiol       Date:  2018-02-01       Impact factor: 3.173

10.  Association between power law coefficients of the anatomical noise power spectrum and lesion detectability in breast imaging modalities.

Authors:  Lin Chen; Craig K Abbey; John M Boone
Journal:  Phys Med Biol       Date:  2013-02-19       Impact factor: 3.609

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