TY - GEN
T1 - A hybrid detection scheme of architectural distortion in mammograms using iris filter and Gabor filter
AU - Yamazaki, Mizuki
AU - Teramoto, Atsushi
AU - Fujita, Hiroshi
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
PY - 2016
Y1 - 2016
N2 - Architectural distortion in mammograms is the most frequently missed finding among breast cancer findings, the improvement of detection accuracy in existing commercial CAD software remains a challenge. In this study, in order to improve the detection accuracy of architectural distortion in mammography, we propose a hybrid automatic detection method that combines with the enhancement method of the concentration of line structure and massive pattern. In the method, the detection of the concentration of the line structure is conducted by the adaptive Gabor filter, and the enhancement of the massive pattern is performed by the iris filter. The concentration index is calculated from these filtered images; the lesion candidate regions are obtained. As for false positive (FP) reduction, 15 shape features are calculated from the candidate regions. Then, they are given to the support vector machine; the candidate regions are classified either as true positive or FP. In the experiment, we compared the results of the proposed method and physician interpretation report using 200 images (63 architectural distortions) from a digital database of screening mammography. Experimental results indicate that our method may be effective to improve the performance of computer aided detection in mammography.
AB - Architectural distortion in mammograms is the most frequently missed finding among breast cancer findings, the improvement of detection accuracy in existing commercial CAD software remains a challenge. In this study, in order to improve the detection accuracy of architectural distortion in mammography, we propose a hybrid automatic detection method that combines with the enhancement method of the concentration of line structure and massive pattern. In the method, the detection of the concentration of the line structure is conducted by the adaptive Gabor filter, and the enhancement of the massive pattern is performed by the iris filter. The concentration index is calculated from these filtered images; the lesion candidate regions are obtained. As for false positive (FP) reduction, 15 shape features are calculated from the candidate regions. Then, they are given to the support vector machine; the candidate regions are classified either as true positive or FP. In the experiment, we compared the results of the proposed method and physician interpretation report using 200 images (63 architectural distortions) from a digital database of screening mammography. Experimental results indicate that our method may be effective to improve the performance of computer aided detection in mammography.
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U2 - 10.1007/978-3-319-41546-8_23
DO - 10.1007/978-3-319-41546-8_23
M3 - Conference contribution
AN - SCOPUS:84977537412
SN - 9783319415451
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 174
EP - 182
BT - Breast Imaging - 13th International Workshop, IWDM 2016, Proceedings
A2 - Lang, Kristina
A2 - Tingberg, Anders
A2 - Timberg, Pontus
PB - Springer Verlag
T2 - 13th International Workshop on Breast Imaging, IWDM 2016
Y2 - 19 June 2016 through 22 June 2016
ER -
