Improvement of mammographic lesion detection by fusion of information from different views

Sophie Paquerault; Nicholas Petrick; Heang-Ping Chan; Berkman Sahiner

doi:10.1117/12.431080

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3 July 2001 Improvement of mammographic lesion detection by fusion of information from different views

Sophie Paquerault, Nicholas Petrick, Heang-Ping Chan, Berkman Sahiner

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Proceedings Volume 4322, Medical Imaging 2001: Image Processing; (2001) https://doi.org/10.1117/12.431080
Event: Medical Imaging 2001, 2001, San Diego, CA, United States

Abstract

In screening mammography, two standard views, craniocaudal (CC) and medio-lateral oblique (MLO), are commonly taken, and radiologists use information from the two views for lesion detection and diagnosis. Current computer-aided diagnosis (CAD) systems are designed to detect lesions on each view separately. We are developing a CAD method that utilizes information from the two views to reduce false-positives (FPs). Our two-view detection scheme consists of two main stages, a one-view pre-screening stage and a two-view correspondence stage. The one-view and two-view scores are then fused to estimate the likelihood that an object is a true mass. In this study, we analyzed the effectiveness of the proposed fusion scheme for FP reduction and its dependence on the number of objects per image in the pre-screening stage. The preliminary results demonstrate that the fusion of information from the CC and MLO views significantly reduced the FP rate in comparison to the one-view scheme. When the pre-screening stage produced 10 objects per image, the two-view fusion technique reduced the FP rate from an average of 2.1 FPs/image in our current one-view CAD scheme to 1.2 FPs/image at a sensitivity of 80%. The results also indicate that the improvement in the detection accuracy was essentially independent of the number of initial objects per image obtained at the pre-screening stage for this data set.

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Sophie Paquerault, Nicholas Petrick, Heang-Ping Chan, and Berkman Sahiner "Improvement of mammographic lesion detection by fusion of information from different views", Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); https://doi.org/10.1117/12.431080

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