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Deformable Mapping Method to Relate Lesions in Dedicated Breast CT Images to Those in Automated Breast Ultrasound and Digital Breast Tomosynthesis Images.
Green, Crystal A; Goodsitt, Mitchell M; Lau, Jasmine H; Brock, Kristy K; Davis, Cynthia L; Carson, Paul L.
Afiliación
  • Green CA; Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI, USA; Department of Radiology, University of Michigan Health System, Ann Arbor, MI, USA. Electronic address: canngree@umich.edu.
  • Goodsitt MM; Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI, USA; Department of Radiology, University of Michigan Health System, Ann Arbor, MI, USA.
  • Lau JH; Department of Radiology, University of Michigan Health System, Ann Arbor, MI, USA.
  • Brock KK; Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Davis CL; General Electric Global Research, Niskayuna, NY, USA.
  • Carson PL; Department of Radiology, University of Michigan Health System, Ann Arbor, MI, USA.
Ultrasound Med Biol ; 46(3): 750-765, 2020 03.
Article en En | MEDLINE | ID: mdl-31806500
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Procesamiento de Imagen Asistido por Computador / Neoplasias de la Mama / Mamografía / Tomografía Computarizada por Rayos X / Ultrasonografía Mamaria Idioma: En Revista: Ultrasound Med Biol Año: 2020 Tipo del documento: Article Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Procesamiento de Imagen Asistido por Computador / Neoplasias de la Mama / Mamografía / Tomografía Computarizada por Rayos X / Ultrasonografía Mamaria Idioma: En Revista: Ultrasound Med Biol Año: 2020 Tipo del documento: Article Pais de publicación: Reino Unido