Using data fusion to characterize breast tissue

Nebojsa Duric; Peter J. Littrup; Richard Leach Jr.; Steve G. Azevedo; James V. Candy; Thomas Moore; David H. Chambers; Jeffrey E. Mast; Earle Holsapple

doi:10.1117/12.462167

11 April 2002 Using data fusion to characterize breast tissue

Nebojsa Duric, Peter J. Littrup, Richard Leach Jr., Steve G. Azevedo, James V. Candy, Thomas Moore, David H. Chambers, Jeffrey E. Mast, Earle Holsapple

Author Affiliations +

Proceedings Volume 4687, Medical Imaging 2002: Ultrasonic Imaging and Signal Processing; (2002) https://doi.org/10.1117/12.462167
Event: Medical Imaging 2002, 2002, San Diego, California, United States

Abstract

New ultrasound data, obtained with a circular experimental scanner, are compared with data obtained with standard X-ray CT. Ultrasound data obtained by scanning fixed breast tissue were used to generate images of sound speed and reflectivity. The ultrasound images exhibit approximately 1 mm resolution and about 20 dB of dynamic range. All data were obtained in a circular geometry. X-ray CT scans were used to generate X-ray images corresponding to the same 'slices' obtained with the ultrasound scanner. The good match of sensitivity, resolution and angular coverage between the ultrasound and X-ray data makes possible a direct comparison of the three types of images. We present the results of such a comparison for an excised breast fixed in formalin. The results are presented visually using various types of data fusion. A general correspondence between the sound speed, reflectivity and X-ray morphologies is found. The degree to which data fusion can help characterize tissue is assessed by examining the quantitative correlations between the ultrasound and X-ray images.

Citation Download Citation

Nebojsa Duric, Peter J. Littrup, Richard Leach Jr., Steve G. Azevedo, James V. Candy, Thomas Moore, David H. Chambers, Jeffrey E. Mast, and Earle Holsapple "Using data fusion to characterize breast tissue", Proc. SPIE 4687, Medical Imaging 2002: Ultrasonic Imaging and Signal Processing, (11 April 2002); https://doi.org/10.1117/12.462167

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