Literature DB >> 9399171

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

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

Abstract

The purpose of this study was to determine whether intensity windowing (IW) improves detection of simulated masses in dense mammograms. Simulated masses were embedded in dense mammograms digitized at 50 microns/pixel, 12 bits deep. Images were printed with no windowing applied and with nine window width and level combinations applied. A simulated mass was embedded in a realistic background of dense breast tissue, with the position of the mass (against the background) varied. The key variables involved in each trial included the position of the mass, the contrast levels and the IW setting applied to the image. Combining the 10 image processing conditions, 4 contrast levels, and 4 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 observers were asked to detect the quadrant of the image into which the mass was located. There was a statistically significant improvement in detection performance for masses when the window width was set at 1024 with a level of 3328. IW should be tested in the clinic to determine whether mass detection performance in real mammograms is improved.

Mesh:

Year:  1997        PMID: 9399171      PMCID: PMC3452985          DOI: 10.1007/bf03168840

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


  15 in total

1.  Digital mammography and related technologies: a perspective from the National Cancer Institute.

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

2.  Lesion conspicuity, structured noise, and film reader error.

Authors:  H L Kundel; G Revesz
Journal:  AJR Am J Roentgenol       Date:  1976-06       Impact factor: 3.959

3.  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
Journal:  Med Phys       Date:  1991 Sep-Oct       Impact factor: 4.071

4.  Psychophysical studies of detection errors in chest radiology.

Authors:  G Revesz; H L Kundel
Journal:  Radiology       Date:  1977-06       Impact factor: 11.105

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.  The influence of structured noise on the detection of radiologic abnormalities.

Authors:  G Revesz; H L Kundel; M A Graber
Journal:  Invest Radiol       Date:  1974 Nov-Dec       Impact factor: 6.016

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.  Adaptive grey level assignment in CT scan display.

Authors:  S M Pizer; J B Zimmerman; E V Staab
Journal:  J Comput Assist Tomogr       Date:  1984-04       Impact factor: 1.826

10.  Enhanced image mammography.

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

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  6 in total

1.  Soft copy display requirements for digital mammography.

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

2.  Comparison of detectability of a simple object with low contrast displayed on a high-brightness color LCD and a monochrome LCD.

Authors:  Keita Takahashi; Junji Morishita; Takeshi Hiwasa; Shiro Hatanaka; Shuji Sakai; Noriyuki Hashimoto; Yasuhiko Nakamura; Fukai Toyofuku; Yoshiharu Higashida; Masafumi Ohki
Journal:  Radiol Phys Technol       Date:  2010-06-12

3.  Detectability of a lung nodule displayed on a liquid-crystal display monitor with different maximum luminance settings.

Authors:  Keita Takahashi; Masaki Sueoka; Yongsu Yoon; Takeshi Hiwasa; Shiro Hatanaka; Yasuhiko Nakamura; Noriyuki Hashimoto; Masafumi Ohki; Junji Morishita
Journal:  Radiol Phys Technol       Date:  2009-09-01

4.  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

5.  Comparison of visual grading and free-response ROC analyses for assessment of image-processing algorithms in digital mammography.

Authors:  F Zanca; C Van Ongeval; F Claus; J Jacobs; R Oyen; H Bosmans
Journal:  Br J Radiol       Date:  2012-07-27       Impact factor: 3.039

6.  Using scientifically and statistically sufficient statistics in comparing image segmentations.

Authors:  Yueh-Yun Chi; Keith E Muller
Journal:  Stat Interface       Date:  2010-01-01       Impact factor: 0.582

  6 in total

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