Title
Optimized acquisition scheme for multi-projection correlation imaging of breast cancer
Abstract
We are reporting the optimized acquisition scheme of multi-projection breast Correlation Imaging (CI) technique, which was pioneered in our lab at Duke University. CI is similar to tomosynthesis in its image acquisition scheme. However, instead of analyzing the reconstructed images, the projection images are directly analyzed for pathology. Earlier, we presented an optimized data acquisition scheme for CI using mathematical observer model. In this article, we are presenting a Computer Aided Detection (CADe)-based optimization methodology. Towards that end, images from 106 subjects recruited for an ongoing clinical trial for tomosynthesis were employed. For each patient, 25 angular projections of each breast were acquired. Projection images were supplemented with a simulated 3 mm 3D lesion. Each projection was first processed by a traditional CADe algorithm at high sensitivity, followed by a reduction of false positives by combining geometrical correlation information available from the multiple images. Performance of the CI system was determined in terms of free-response receiver operating characteristics (FROC) curves and the area under ROC curves. For optimization, the components of acquisition such as the number of projections, and their angular span were systematically changed to investigate which one of the many possible combinations maximized the sensitivity and specificity. Results indicated that the performance of the CI system may be maximized with 7-11 projections spanning an angular arc of 44.8 degrees, confirming our earlier findings using observer models. These results indicate that an optimized CI system may potentially be an important diagnostic tool for improved breast cancer detection.
Year
DOI
Venue
2008
10.1117/12.773174
PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE)
Keywords
Field
DocType
multi-projection imaging,Correlation Imaging,breast tomosynthesis,FROC,CADe
Computer vision,Tomosynthesis,Receiver operating characteristic,Breast imaging,Computer science,Computer-aided diagnosis,Data acquisition,Correlation,Artificial intelligence,Observer (quantum physics),False positive paradox
Conference
Volume
ISSN
Citations 
6915
0277-786X
0
PageRank 
References 
Authors
0.34
1
5
Name
Order
Citations
PageRank
Amarpreet S. Chawla1103.65
Ehsan Samei22814.00
rob saunders310.96
Joseph Y. Lo426127.03
Swatee Singh5112.84