caa a22 4500 463178475 CHVBK 20180406164832.0 cr unu---uuuuu 170326e20070901xx s 000 0 eng 10.1007/s10278-006-0860-9 doi (NATIONALLICENCE)springer-10.1007/s10278-006-0860-9 Fractal Analysis of Contours of Breast Masses in Mammograms [Elektronische Daten] [Rangaraj Rangayyan, Thanh Nguyen] Fractal analysis has been shown to be useful in image processing for characterizing shape and gray-scale complexity. Breast masses present shape and gray-scale characteristics that vary between benign masses and malignant tumors in mammograms. Limited studies have been conducted on the application of fractal analysis specifically for classifying breast masses based on shape. The fractal dimension of the contour of a mass may be computed either directly from the 2-dimensional (2D) contour or from a 1-dimensional (1D) signature derived from the contour. We present a study of four methods to compute the fractal dimension of the contours of breast masses, including the ruler method and the box counting method applied to 1D and 2D representations of the contours. The methods were applied to a data set of 111 contours of breast masses. Receiver operating characteristics (ROC) analysis was performed to assess and compare the performance of fractal dimension and four previously developed shape factors in the classification of breast masses as benign or malignant. Fractal dimension was observed to complement the other shape factors, in particular fractional concavity, in the representation of the complexity of the contours. The combination of fractal dimension with fractional concavity yielded the highest area (A z ) under the ROC curve of 0.93; the two measures, on their own, resulted in A z values of 0.89 and 0.88, respectively. SCAR (Society for Computer Applications in Radiology), 2007 Box counting method nationallicence breast cancer nationallicence breast masses nationallicence breast tumors nationallicence contour analysis nationallicence fractal analysis nationallicence fractal dimension nationallicence ruler method nationallicence shape analysis nationallicence signatures of contours nationallicence Rangayyan Rangaraj Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, T2N 1N4, Calgary, Alberta, Canada aut Nguyen Thanh Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, T2N 1N4, Calgary, Alberta, Canada aut Journal of Digital Imaging Springer-Verlag; http://www.springer-ny.com 20/3(2007-09-01), 223-237 0897-1889 20:3<223 2007 20 10278 https://doi.org/10.1007/s10278-006-0860-9 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10278-006-0860-9 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, Alberta, Canada aut NATIONALLICENCE 700 1- Nguyen Thanh Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, T2N 1N4, Calgary, Alberta, Canada aut NATIONALLICENCE 773 0- Journal of Digital Imaging Springer-Verlag; http://www.springer-ny.com 20/3(2007-09-01), 223-237 0897-1889 20:3<223 2007 20 10278 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer