Computer aided detection (CADe) systems often present multiple false-positives per image in projection mammography due to overlapping anatomy. To reduce the number of such false-positives, we propose performing CADe on image pairs acquired using a bi-plane correlation imaging (BCI) technique. In this technique, images are acquired of each breast at two different projection angles. A traditional CADe algorithm operates on each image to identify suspected lesions. The suspicious areas from both projections are then geometrically correlated, eliminating any lesion that is not identified on both views. Proof of concept studies showed that that the BCI technique reduced the numbers of false-positives per case up to 70%.
The objective of this study was to implement and evaluate the performance of a biplane correlation imaging (BCI) technique aimed to reduce the effect of anatomic noise and improve the detection of lung nodules in chest radiographs. Seventy-one low-dose posterior-anterior images were acquired from an anthropomorphic chest phantom with 0.28°a ngular separations over a range of ±10°along the vertical axis within an 11 s interval. Similar data were acquired from 19 human subjects with institutional review board approval and informed consent. The data were incorporated into a computer-aided detection (CAD) algorithm in which suspect lesions were identified by examining the geometrical correlation of the detected signals that remained relatively constant against variable anatomic backgrounds. The data were analyzed to determine the effect of angular separation, and the overall sensitivity and false-positives for lung nodule detection. The best performance was achieved for angular separations of the projection pairs greater than 5°. Within that range, the technique provided an order of magnitude decrease in the number of false-positive reports when compared with CAD analysis of single-view images. Overall, the technique yielded~1.1 false-positive per patient with an average sensitivity of 75%. The results indicated that the incorporation of angular information can offer a reduction in the number of false-positives without a notable reduction in sensitivity. The findings suggest that the BCI technique has the potential for clinical implementation as a cost-effective technique to improve the detection of subtle lung nodules with lowered rate of false-positives.
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