@article{2cdedd0ab6e84de9a47eb702bc7bb06c,
title = "Deformable Mapping Method to Relate Lesions in Dedicated Breast CT Images to Those in Automated Breast Ultrasound and Digital Breast Tomosynthesis Images",
abstract = "This work demonstrates the potential for using a deformable mapping method to register lesions between dedicated breast computed tomography (bCT) and both automated breast ultrasound (ABUS) and digital breast tomosynthesis (DBT) images (craniocaudal [CC] and mediolateral oblique [MLO] views). Two multi-modality breast phantoms with external fiducial markers attached were imaged by the three modalities. The DBT MLO view was excluded for the second phantom. The automated deformable mapping algorithm uses biomechanical modeling to determine corresponding lesions based on distances between their centers of mass (dCOM) in the deformed bCT model and the reference model (DBT or ABUS). For bCT to ABUS, the mean dCOM was 5.2 ± 2.6 mm. For bCT to DBT (CC), the mean dCOM was 5.1 ± 2.4 mm. For bCT to DBT (MLO), the mean dCOM was 4.7 ± 2.5 mm. This application could help improve a radiologist's efficiency and accuracy in breast lesion characterization, using multiple imaging modalities.",
keywords = "Automated breast ultrasound, Biomechanical modeling, Breast CT, Breast imaging, Deformable registration, Digital breast tomosynthesis, External markers, Multi-modality",
author = "Green, {Crystal A.} and Goodsitt, {Mitchell M.} and Lau, {Jasmine H.} and Brock, {Kristy K.} and Davis, {Cynthia L.} and Carson, {Paul L.}",
note = "Funding Information: M. Goodsitt is a co-investigator on a grant funded by GE Healthcare. C. Davis is an employee of General Electric Corporation and holds several US patents on medical imaging. M. Goodsitt and P. Carson are collaborators on research with GE Global Research, Niskayuna, NY. Funding Information: This work was supported in part by a research grant (15-PAF04328) from GE Global Research. Crystal A. Green is supported by the Science, Mathematics and Research for Transformation (SMART) Scholarship for Service Program (HQ0034-16-C-0008). The authors would like to thank Ted Lynch, Ph.D. of CIRS, Inc. for his assistance in phantom development and characterization. M. Goodsitt is a co-investigator on a grant funded by GE Healthcare. C. Davis is an employee of General Electric Corporation and holds several US patents on medical imaging. M. Goodsitt and P. Carson are collaborators on research with GE Global Research, Niskayuna, NY. Funding Information: This work was supported in part by a research grant (15-PAF04328) from GE Global Research. Crystal A. Green is supported by the Science, Mathematics and Research for Transformation (SMART) Scholarship for Service Program (HQ0034-16-C-0008). The authors would like to thank Ted Lynch, Ph.D. of CIRS, Inc., for his assistance in phantom development and characterization. Publisher Copyright: {\textcopyright} 2019 World Federation for Ultrasound in Medicine & Biology",
year = "2020",
month = mar,
doi = "10.1016/j.ultrasmedbio.2019.10.016",
language = "English (US)",
volume = "46",
pages = "750--765",
journal = "Ultrasound in Medicine and Biology",
issn = "0301-5629",
publisher = "Elsevier USA",
number = "3",
}