naa a22 4500 510807968 CHVBK 20180411083427.0 cr unu---uuuuu 180411e20130701xx s 000 0 eng 10.1007/s11548-012-0793-3 doi (NATIONALLICENCE)springer-10.1007/s11548-012-0793-3 Measures of divergence of oriented patterns for the detection of architectural distortion in prior mammograms [Elektronische Daten] [Rangaraj Rangayyan, Shantanu Banik, Jayasree Chakraborty, Sudipta Mukhopadhyay, J. Desautels] Purpose We propose a method for the detection of architectural distortion in prior mammograms of interval-cancer cases based on the expected orientation of breast tissue patterns in mammograms. Methods The expected orientation of the breast tissue at each pixel was derived by using automatically detected landmarks including the breast boundary, the nipple, and the pectoral muscle (in mediolateral-oblique views). We hypothesize that the presence of architectural distortion changes the normal expected orientation of breast tissue patterns in a mammographic image. The angular deviation of the oriented structures in a given mammogram as compared to the expected orientation was analyzed to detect potential sites of architectural distortion using a measure of divergence of oriented patterns. Each potential site of architectural distortion was then characterized using measures of spicularity and angular dispersion specifically designed to represent spiculating patterns. The novel features for the characterization of spiculating patterns include an index of divergence of spicules computed from the intensity image and Gabor magnitude response using the Gabor angle response; radially weighted difference and angle-weighted difference (AWD) measures of the intensity, Gabor magnitude, and Gabor angle response; and AWD in the entropy of spicules computed from the intensity, Gabor magnitude, and Gabor angle response. Results Using the newly proposed features with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases, through feature selection and pattern classification with an artificial neural network, an area under the receiver operating characteristic curve of 0.75 was obtained. Free-response receiver operating characteristic analysis indicated a sensitivity of 0.80 at 5.3 false positives (FPs) per patient. Combining the features proposed in the present paper with others described in our previous works led to significant improvement with a sensitivity of 0.80 at 3.7 FPs per patient. Conclusion The proposed methods can detect architectural distortion in prior mammograms taken 15 months (on the average) before clinical diagnosis of breast cancer, but the FP rate needs to be reduced. CARS, 2012 Angular dispersion nationallicence Architectural distortion nationallicence Breast cancer nationallicence Coherence nationallicence Computer-aided diagnosis (CAD) nationallicence Divergence of oriented patterns nationallicence Gabor filters nationallicence Oriented texture nationallicence Prior mammograms nationallicence Spicularity nationallicence Rangayyan Rangaraj Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, T2N 1N4, Calgary, AB, Canada aut Banik Shantanu Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, T2N 1N4, Calgary, AB, Canada aut Chakraborty Jayasree Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, T2N 1N4, Calgary, AB, Canada aut Mukhopadhyay Sudipta Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology Kharagpur, 721 302, Kharagpur, West Bengal, India aut Desautels J. Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, T2N 1N4, Calgary, AB, Canada aut International Journal of Computer Assisted Radiology and Surgery Springer Berlin Heidelberg 8/4(2013-07-01), 527-545 1861-6410 8:4<527 2013 8 11548 https://doi.org/10.1007/s11548-012-0793-3 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11548-012-0793-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Rangayyan Rangaraj Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, T2N 1N4, Calgary, AB, Canada aut NATIONALLICENCE 700 1- Banik Shantanu Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, T2N 1N4, Calgary, AB, Canada aut NATIONALLICENCE 700 1- Chakraborty Jayasree Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, T2N 1N4, Calgary, AB, Canada aut NATIONALLICENCE 700 1- Mukhopadhyay Sudipta Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology Kharagpur, 721 302, Kharagpur, West Bengal, India aut NATIONALLICENCE 700 1- Desautels J. Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, T2N 1N4, Calgary, AB, Canada aut NATIONALLICENCE 773 0- International Journal of Computer Assisted Radiology and Surgery Springer Berlin Heidelberg 8/4(2013-07-01), 527-545 1861-6410 8:4<527 2013 8 11548 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer