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Mary S Soo

Showing results (1-10 of 12) with videos related to

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Ultrasonic Imaging|May 4, 2005
Clinical evaluation of combined spatial compounding and adaptive imaging in breast tissueJeremy J Dahl, Mary S Soo, Gregg E Trahey
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control|November 16, 2005
Spatial and temporal aberrator stability for real-time adaptive imagingJeremy J Dahl, Mary S Soo, Gregg E Trahey
AJR. American Journal of Roentgenology|March 25, 2005
BI-RADS for sonography: positive and negative predictive values of sonographic featuresAndrea S Hong, Eric L Rosen, Mary S Soo, et al.
Academic Radiology|March 31, 2012
Suspicious breast lesions detected at 3.0 T magnetic resonance imaging: clinical and histological outcomesKaren S Johnson, Jay A Baker, Sheila S Lee, et al.
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control|October 14, 2006
Adaptive imaging on a diagnostic ultrasound scanner at quasi real-time ratesJeremy J Dahl, Stephen A McAleavey, Gianmarco F Pinton, et al.
Radiology|October 18, 2014
Can breast cancer molecular subtype help to select patients for preoperative MR imaging?Lars J Grimm, Karen S Johnson, P Kelly Marcom, et al.
Academic Radiology|July 9, 2015
Abbreviated screening protocol for breast MRI: a feasibility studyLars J Grimm, Mary S Soo, Sora Yoon, et al.
The Breast Journal|March 16, 2017
Relationships Between MRI Breast Imaging-Reporting and Data System (BI-RADS) Lexicon Descriptors and Breast Cancer Molecular Subtypes: Internal Enhancement is Associated with Luminal B SubtypeLars J Grimm, Jing Zhang, Jay A Baker, et al.
Academic Radiology|February 10, 2009
The influence of increased ambient lighting on mass detection in mammogramsBenjamin J Pollard, Ehsan Samei, Amarpreet S Chawla, et al.
Journal of Magnetic Resonance Imaging : JMRI|January 17, 2019
Machine learning-based prediction of future breast cancer using algorithmically measured background parenchymal enhancement on high-risk screening MRIAshirbani Saha, Lars J Grimm, Sujata V Ghate, et al.
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
Ultrasonic Imaging|May 4, 2005
Clinical evaluation of combined spatial compounding and adaptive imaging in breast tissueJeremy J Dahl, Mary S Soo, Gregg E Trahey
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control|November 16, 2005
Spatial and temporal aberrator stability for real-time adaptive imagingJeremy J Dahl, Mary S Soo, Gregg E Trahey
AJR. American Journal of Roentgenology|March 25, 2005
BI-RADS for sonography: positive and negative predictive values of sonographic featuresAndrea S Hong, Eric L Rosen, Mary S Soo, et al.
Academic Radiology|March 31, 2012
Suspicious breast lesions detected at 3.0 T magnetic resonance imaging: clinical and histological outcomesKaren S Johnson, Jay A Baker, Sheila S Lee, et al.
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control|October 14, 2006
Adaptive imaging on a diagnostic ultrasound scanner at quasi real-time ratesJeremy J Dahl, Stephen A McAleavey, Gianmarco F Pinton, et al.
Radiology|October 18, 2014
Can breast cancer molecular subtype help to select patients for preoperative MR imaging?Lars J Grimm, Karen S Johnson, P Kelly Marcom, et al.
Academic Radiology|July 9, 2015
Abbreviated screening protocol for breast MRI: a feasibility studyLars J Grimm, Mary S Soo, Sora Yoon, et al.
The Breast Journal|March 16, 2017
Relationships Between MRI Breast Imaging-Reporting and Data System (BI-RADS) Lexicon Descriptors and Breast Cancer Molecular Subtypes: Internal Enhancement is Associated with Luminal B SubtypeLars J Grimm, Jing Zhang, Jay A Baker, et al.
Academic Radiology|February 10, 2009
The influence of increased ambient lighting on mass detection in mammogramsBenjamin J Pollard, Ehsan Samei, Amarpreet S Chawla, et al.
Journal of Magnetic Resonance Imaging : JMRI|January 17, 2019
Machine learning-based prediction of future breast cancer using algorithmically measured background parenchymal enhancement on high-risk screening MRIAshirbani Saha, Lars J Grimm, Sujata V Ghate, et al.
Pageof 2