Literature DB >> 9165422

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

E D Pisano1, J Chandramouli, B M Hemminger, M DeLuca, D Glueck, R E Johnston, K Muller, M P Braeuning, S Pizer.   

Abstract

This study attempts to determine whether intensity windowing (IW) improves detection of simulated calcifications in dense mammograms. Clusters of five simulated calcifications were embedded in dense mammograms digitized at 50-microns pixels, 12 bits deep. Film images with no windowing applied were compared with film images with nine different window widths and levels applied. A simulated cluster was embedded in a realistic background of dense breast tissue, with the position of the cluster varied. The key variables involved in each trial included the position of the cluster, contrast level of the cluster, and the IW settings applied to the image. Combining the ten IW conditions, four contrast levels and four quadrant positions gave 160 combinations. The trials were constructed by pairing 160 combinations of key variables with 160 backgrounds. The entire experiment consisted of 800 trials. Twenty student observers were asked to detect the quadrant of the image in which the mass was located. There was a statistically significant improvement in detection performance for clusters of calcifications when the window width was set at 1024 with a level of 3328, and when the window width was set at 1024 with a level of 3456. The selected IW settings should be tested in the clinic with digital mammograms to determine whether calcification detection performance can be improved.

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Year:  1997        PMID: 9165422      PMCID: PMC3453001          DOI: 10.1007/bf03168559

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  13 in total

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Authors:  F Shtern
Journal:  Radiology       Date:  1992-06       Impact factor: 11.105

2.  Computerized detection of masses in digital mammograms: analysis of bilateral subtraction images.

Authors:  F F Yin; M L Giger; K Doi; C E Metz; C J Vyborny; R A Schmidt
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3.  Psychophysical studies of detection errors in chest radiology.

Authors:  G Revesz; H L Kundel
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4.  Digital mammography. ROC studies of the effects of pixel size and unsharp-mask filtering on the detection of subtle microcalcifications.

Authors:  H P Chan; C J Vyborny; H MacMahon; C E Metz; K Doi; E A Sickles
Journal:  Invest Radiol       Date:  1987-07       Impact factor: 6.016

5.  Image feature analysis and computer-aided diagnosis in digital radiography. I. Automated detection of microcalcifications in mammography.

Authors:  H P Chan; K Doi; S Galhotra; C J Vyborny; H MacMahon; P M Jokich
Journal:  Med Phys       Date:  1987 Jul-Aug       Impact factor: 4.071

6.  Portal film enhancement: technique and clinical utility.

Authors:  J Rosenman; C A Roe; R Cromartie; K E Muller; S M Pizer
Journal:  Int J Radiat Oncol Biol Phys       Date:  1993-01-15       Impact factor: 7.038

7.  A method for determination of optimal image enhancement for the detection of mammographic abnormalities.

Authors:  D T Puff; E D Pisano; K E Muller; R E Johnston; B M Hemminger; C A Burbeck; R McLelland; S M Pizer
Journal:  J Digit Imaging       Date:  1994-11       Impact factor: 4.056

8.  Comparison of bilateral-subtraction and single-image processing techniques in the computerized detection of mammographic masses.

Authors:  F F Yin; M L Giger; C J Vyborny; K Doi; R A Schmidt
Journal:  Invest Radiol       Date:  1993-06       Impact factor: 6.016

9.  Enhanced image mammography.

Authors:  M B McSweeney; P Sprawls; R L Egan
Journal:  AJR Am J Roentgenol       Date:  1983-01       Impact factor: 3.959

10.  Selective digital enhancement of conventional film mammography.

Authors:  D A Hale; J F Cook; Z Baniqued; A Silva-Hale; M Molloy; R H Pearl; N C Hadro; D P Jaques
Journal:  J Surg Oncol       Date:  1994-01       Impact factor: 3.454

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  3 in total

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Authors:  Bradley M Hemminger
Journal:  J Digit Imaging       Date:  2003-12-15       Impact factor: 4.056

2.  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

3.  Breast imaging in the new era.

Authors:  K Planche; S Vinnicombe
Journal:  Cancer Imaging       Date:  2004-01-12       Impact factor: 3.909

  3 in total

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