Literature DB >> 6336871

Enhanced image mammography.

M B McSweeney, P Sprawls, R L Egan.   

Abstract

A blurred mass subtraction technique has been developed for mammography that will enhance small object contrast and visibility throughout the breast area. The procedure is easy to implement and requires no additional exposure. Perception of low-contrast objects is improved by eliminating extreme light and dark image areas. Contrast of structures within certain parts of the breast is increased by compression into the high-contrast part of the film characteristic curve. Detail visibility is also increased by the edge enhancement produced by this process. This paper describes the enhancement process and gives an analysis of its capabilities and limitations.

Mesh:

Year:  1983        PMID: 6336871     DOI: 10.2214/ajr.140.1.9

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  6 in total

1.  Contrast limited adaptive histogram equalization image processing to improve the detection of simulated spiculations in dense mammograms.

Authors:  E D Pisano; S Zong; B M Hemminger; M DeLuca; R E Johnston; K Muller; M P Braeuning; S M Pizer
Journal:  J Digit Imaging       Date:  1998-11       Impact factor: 4.056

2.  The effect of intensity windowing on the detection of simulated masses embedded in dense portions of digitized mammograms in a laboratory setting.

Authors:  E D Pisano; J Chandramouli; B M Hemminger; D Glueck; R E Johnston; K Muller; M P Braeuning; D Puff; W Garrett; S Pizer
Journal:  J Digit Imaging       Date:  1997-11       Impact factor: 4.056

3.  Does intensity windowing improve the detection of simulated calcifications in dense mammograms?

Authors:  E D Pisano; J Chandramouli; B M Hemminger; M DeLuca; D Glueck; R E Johnston; K Muller; M P Braeuning; S Pizer
Journal:  J Digit Imaging       Date:  1997-05       Impact factor: 4.056

Review 4.  Clinical use of digital mammography: the present and the prospects.

Authors:  R A Schmidt; R M Nishikawa
Journal:  J Digit Imaging       Date:  1995-02       Impact factor: 4.056

5.  Bayesian classifier with simplified learning phase for detecting microcalcifications in digital mammograms.

Authors:  Imad Zyout; Ikhlas Abdel-Qader; Christina Jacobs
Journal:  Int J Biomed Imaging       Date:  2010-01-04

6.  Breast phantom with silicone implant for evaluation in conventional mammography.

Authors:  Fábio A R Silva; Luíza F Souza; Carlos E G Salmon; Divanizia N Souza
Journal:  J Appl Clin Med Phys       Date:  2010-09-20       Impact factor: 2.102

  6 in total

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