Characterizing Architectural Distortion in Mammograms by Linear Saliency

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• 作者：Fabián Narváez ; Jorge Alvarez ; Juan D. Garcia-Arteaga…
• 关键词：Breast spiculated lesions ; Architectural distortion ; Mammography ; Linear saliency
• 刊名：Journal of Medical Systems
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：41
• 期：2
• 全文大小：
• 刊物类别：Mathematics and Statistics
• 刊物主题：Health Informatics; Health Informatics; Statistics for Life Sciences, Medicine, Health Sciences;
• 出版者：Springer US
• ISSN：1573-689X
• 卷排序：41

文摘

Architectural distortion (AD) is a common cause of false-negatives in mammograms. This lesion usually consists of a central retraction of the connective tissue and a spiculated pattern radiating from it. This pattern is difficult to detect due the complex superposition of breast tissue. This paper presents a novel AD characterization by representing the linear saliency in mammography Regions of Interest (ROI) as a graph composed of nodes corresponding to locations along the ROI boundary and edges with a weight proportional to the line intensity integrals along the path connecting any pair of nodes. A set of eigenvectors from the adjacency matrix is then used to extract discriminant coefficients that represent those nodes with higher salient lines. A dimensionality reduction is further accomplished by selecting the pair of nodes with major contribution for each of the computed eigenvectors. The set of main salient lines is then assembled as a feature vector that inputs a conventional Support Vector Machine (SVM). Experimental results with two benchmark databases, the mini-MIAS and DDSM databases, demonstrate that the proposed linear saliency domain method (LSD) performs well in terms of accuracy. The approach was evaluated with a set of 246 RoI extracted from the DDSM (123 normal tissues and 123 AD) and a set of 38 ROI from the mini-MIAS collections (19 normal tissues and 19 AD) respectively. The classification results showed respectively for both databases an accuracy rate of 89 % and 87 %, a sensitivity rate of 85 % and 95 %, and a specificity rate of 93 % and 84 %. Likewise, the area under curve (A_z) of the Receiver Operating Characteristic (ROC) curve was 0.93 for both databases.