Digital breast tomosynthesis: Application of 2D digital mammography CAD to detection of microcalcification clusters on planar projection image

被引:0
|
作者
Samala, Ravi K. [1 ]
Chan, Heang-Ping [1 ]
Lu, Yao [1 ]
Hadjiiski, Lubomir [1 ]
Wei, Jun [1 ]
Helvie, Mark [1 ]
机构
[1] Univ Michigan, Ann Arbor, MI 48109 USA
来源
MEDICAL IMAGING 2015: COMPUTER-AIDED DIAGNOSIS | 2015年 / 9414卷
关键词
digital breast tomosynthesis; planar projection image; computer-aided detection; microcalcification clusters; digital mammography; nonparametric analysis; JAFROC; COMPUTER-AIDED DETECTION;
D O I
10.1117/12.2076291
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Computer-aided detection (CAD) has the potential to aid radiologists in detection of microcalcification clusters (MCs). CAD for digital breast tomosynthesis (DBT) can be developed by using the reconstructed volume, the projection views or other derivatives as input. We have developed a novel method of generating a single planar projection (PPJ) image from a regularized DBT volume to emphasize the high contrast objects such as microcalcifications while removing the anatomical background and noise. In this work, we adapted a CAD system developed for digital mammography (CAD(DM)) to the PPJ image and compared its performance with our CAD system developed for DBT volumes (CAD(DBT)) in the same set of cases. For microcalcification detection in the PPJ image using the CAD(DM) system, the background removal preprocessing step designed for DM was not needed. The other methods and processing steps in the CAD(DM) system were kept without modification while the parameters were optimized with a training set. The linear discriminant analysis classifier using cluster based features was retrained to generate a discriminant score to be used as decision variable. For view-based FROC analysis, at 80% sensitivity, an FP rate of 1.95/volume and 1.54/image were achieved, respectively, for CAD(DBT) and CAD(DM) in an independent test set. At a threshold of 1.2 FPs per image or per (DBT) volume, the nonparametric analysis of the area under the FROC curve shows that the optimized CAD(DM) for PPJ is significantly better than CAD(DBT). However, the performance of CAD(DM) drops at higher sensitivity or FP rate, resulting in similar overall performance between the two CAD systems. The higher sensitivity of the CAD(DM) in the low FP rate region and vice versa for the CAD(DBT) indicate that a joint CAD system combining detection in the DBT volume and the PPJ image has the potential to increase the sensitivity and reduce the FP rate.
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页数:7
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