Radiology
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


This Article
Right arrow Full Text (PDF)
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by te Brake, G. M.
Right arrow Articles by Hendriks, J. H.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by te Brake, G. M.
Right arrow Articles by Hendriks, J. H.

Radiology, Vol 207, 465-471, Copyright © 1998 by Radiological Society of North America


ARTICLES

Automated detection of breast carcinomas not detected in a screening program

GM te Brake, N Karssemeijer and JH Hendriks
Department of Radiology, Radboud University Hospital, Nijmegen, The Netherlands.

PURPOSE: To investigate the possibility of automated detection of early signs of cancer that were not detected in a breast cancer screening program. MATERIALS AND METHODS: A set of 75 mammograms (in 65 women) with subtle circumscribed masses, stellate lesions, and architectural distortions that were not detected in a screening program by two radiologists was assembled and extended with 142 normal mammograms (contralateral mammograms in the same 65 women). An automated system for the detection of circumscribed masses and stellate lesions was applied to this set. RESULTS: In 22 (34%) of 65 cases, an early sign of cancer was detected at a specificity of one false-positive finding per image. At a specificity of three false-positive findings per image, 39 (60%) of the cancers were detected. Of the tumors that were classified as screening errors, seven (50%) were found at a specificity of 0.5 false-positive finding per image. CONCLUSION: A substantial proportion of cancers that were missed in a screening program, despite double reading, were found with this detection method at less than one false- positive finding per image.


This article has been cited by other articles:


Home page
RadiologyHome page
F. J. Gilbert, S. M. Astley, M. A. McGee, M. G. C. Gillan, C. R. M. Boggis, P. M. Griffiths, and S. W. Duffy
Single Reading with Computer-aided Detection and Double Reading of Screening Mammograms in the United Kingdom National Breast Screening Program
Radiology, October 1, 2006; 241(1): 47 - 53.
[Abstract] [Full Text] [PDF]


Home page
Am. J. Roentgenol.Home page
T. E. Cupples, J. E. Cunningham, and J. C. Reynolds
Impact of Computer-Aided Detection in a Regional Screening Mammography Program
Am. J. Roentgenol., October 1, 2005; 185(4): 944 - 950.
[Abstract] [Full Text] [PDF]


Home page
RadiologyHome page
M. A. Helvie, L. Hadjiiski, E. Makariou, H.-P. Chan, N. Petrick, B. Sahiner, S.-C. B. Lo, M. Freedman, D. Adler, J. Bailey, et al.
Sensitivity of Noncommercial Computer-aided Detection System for Mammographic Breast Cancer Detection: Pilot Clinical Trial
Radiology, April 1, 2004; 231(1): 208 - 214.
[Abstract] [Full Text] [PDF]


Home page
RadiologyHome page
N. Karssemeijer, J. D. M. Otten, A. L. M. Verbeek, J. H. Groenewoud, H. J. de Koning, J. H. C. L. Hendriks, and R. Holland
Computer-aided Detection versus Independent Double Reading of Masses on Mammograms
Radiology, April 1, 2003; 227(1): 192 - 200.
[Abstract] [Full Text] [PDF]


Home page
Am. J. Roentgenol.Home page
J. Eng
Predicting the Presence of Acute Pulmonary Embolism: A Comparative Analysis of the Artificial Neural Network, Logistic Regression, and Threshold Models
Am. J. Roentgenol., October 1, 2002; 179(4): 869 - 874.
[Abstract] [Full Text] [PDF]


Home page
RadiologyHome page
T. W. Freer and M. J. Ulissey
Screening Mammography with Computer-aided Detection: Prospective Study of 12,860 Patients in a Community Breast Center
Radiology, September 1, 2001; 220(3): 781 - 786.
[Abstract] [Full Text] [PDF]


Home page
RadiologyHome page
C. J. Vyborny, T. Doi, K. F. O'Shaughnessy, H. M. Romsdahl, A. C. Schneider, and A. A. Stein
Breast Cancer: Importance of Spiculation in Computer-aided Detection
Radiology, June 1, 2000; 215(3): 703 - 707.
[Abstract] [Full Text]


Home page
RadiologyHome page
B. Zheng, M. A. Ganott, C. A. Britton, C. M. Hakim, L. A. Hardesty, T. S. Chang, H. E. Rockette, and D. Gur
Soft-Copy Mammographic Readings with Different Computer-assisted Detection Cuing Environments: Preliminary Findings
Radiology, December 1, 2001; 221(3): 633 - 640.
[Abstract] [Full Text] [PDF]




HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
RADIOLOGY RADIOGRAPHICS RSNA JOURNALS ONLINE
Copyright © 1998 by the Radiological Society of North America.