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Proceedings Paper

Combination of conspicuity improved synthetic mammograms and digital breast tomosynthesis: a promising approach for mass detection
Author(s): Seong Tae Kim; Dae Hoe Kim; Yong Man Ro
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Paper Abstract

In this study, a novel mass detection framework that utilizes the information from synthetic mammograms has been developed for detecting masses in digital breast tomosynthesis (DBT). In clinical study, it is demonstrated that the combination of DBT and full field digital mammography (FFDM) increases the reader performance. To reduce the radiation dose in this approach, synthetic mammogram has been developed in previous researches and it is demonstrated that synthetic mammogram can alternate the FFDM when it is used with DBT. In this study, we investigate the feasibility of the combined approach of DBT and synthetic mammogram in point of computer-aided detection (CAD). As a synthetic mammogram, two-dimensional image was generated by adopting conspicuous voxels of three-dimensional DBT volume in our study. The mass likelihood scores estimated for each mass candidates in synthetic mammogram and DBT are merged to differentiate masses and false positives (FPs) in combined approach. We compared the performance of detecting masses in the proposed combined approach and DBT alone. A clinical data set of 196 DBT volumes was used to evaluate the different detection schemes. The combined approach achieved sensitivity of 80% and 89% with 1.16 and 2.37 FPs per DBT volume. The DBT alone approach achieved same sensitivities with 1.61 and 3.46 FPs per DBT volume. Experimental results show that statistically significant improvement (p = 0.002) is achieved in combined approach compared to DBT alone. These results imply that the information fusion of synthetic mammogram and DBT is a promising approach to detect masses in DBT.

Paper Details

Date Published: 20 March 2015
PDF: 6 pages
Proc. SPIE 9414, Medical Imaging 2015: Computer-Aided Diagnosis, 941419 (20 March 2015); doi: 10.1117/12.2081854
Show Author Affiliations
Seong Tae Kim, KAIST (Korea, Republic of)
Dae Hoe Kim, KAIST (Korea, Republic of)
Yong Man Ro, KAIST (Korea, Republic of)

Published in SPIE Proceedings Vol. 9414:
Medical Imaging 2015: Computer-Aided Diagnosis
Lubomir M. Hadjiiski; Georgia D. Tourassi, Editor(s)

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