Abstract:
:Architectural distortion is an important sign of breast cancer, but because of its subtlety, it is a common cause of false-negative findings on screening mammograms. This paper presents methods for the detection of architectural distortion in mammograms of interval cancer cases taken prior to the detection of breast cancer using Gabor filters, phase portrait analysis, fractal analysis, and texture analysis. The methods were used to detect initial candidates for sites of architectural distortion in prior mammograms of interval cancer and also normal control cases. A total of 4,224 regions of interest (ROIs) were automatically obtained from 106 prior mammograms of 56 interval cancer cases, including 301 ROIs related to architectural distortion, and from 52 prior mammograms of 13 normal cases. For each ROI, the fractal dimension and Haralick's texture features were computed. Feature selection was performed separately using stepwise logistic regression and stepwise regression. The best results achieved, in terms of the area under the receiver operating characteristics curve, with the features selected by stepwise logistic regression are 0.76 with the Bayesian classifier, 0.73 with Fisher linear discriminant analysis, 0.77 with an artificial neural network based on radial basis functions, and 0.77 with a support vector machine. Analysis of the performance of the methods with free-response receiver operating characteristics indicated a sensitivity of 0.80 at 7.6 false positives per image. The methods have good potential in detecting architectural distortion in mammograms of interval cancer cases.
journal_name
J Digit Imagingjournal_title
Journal of digital imagingauthors
Rangayyan RM,Banik S,Desautels JEdoi
10.1007/s10278-009-9257-xsubject
Has Abstractpub_date
2010-10-01 00:00:00pages
611-31issue
5eissn
0897-1889issn
1618-727Xjournal_volume
23pub_type
杂志文章abstract::We propose the design of a teaching system named Interpretation and Diagnosis of Mammograms (INDIAM) for training students in the interpretation of mammograms and diagnosis of breast cancer. The proposed system integrates an illustrated tutorial on radiology of the breast, that is, mammography, which uses education te...
journal_title:Journal of digital imaging
pub_type: 杂志文章
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journal_title:Journal of digital imaging
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journal_title:Journal of digital imaging
pub_type: 杂志文章
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journal_title:Journal of digital imaging
pub_type: 杂志文章
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journal_title:Journal of digital imaging
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journal_title:Journal of digital imaging
pub_type: 杂志文章
doi:10.1007/BF03168176
更新日期:1998-11-01 00:00:00
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journal_title:Journal of digital imaging
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journal_title:Journal of digital imaging
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journal_title:Journal of digital imaging
pub_type: 杂志文章
doi:10.1007/s10278-016-9869-x
更新日期:2016-10-01 00:00:00
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journal_title:Journal of digital imaging
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journal_title:Journal of digital imaging
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journal_title:Journal of digital imaging
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journal_title:Journal of digital imaging
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journal_title:Journal of digital imaging
pub_type: 杂志文章
doi:10.1007/s10278-018-0146-z
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journal_title:Journal of digital imaging
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