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Journal of the American College of Surgeons|February 8, 2018
Pathologic Upgrade Rates of High-Risk Breast Lesions on Digital Two-Dimensional vs Tomosynthesis MammographyLeslie R Lamb, Manisha Bahl, Kevin S Hughes, et al.AJR. American Journal of Roentgenology|November 21, 2015
Architectural Distortion on Mammography: Correlation With Pathologic Outcomes and Predictors of MalignancyManisha Bahl, Jay A Baker, Emily N Kinsey, et al.AJR. American Journal of Roentgenology|February 14, 2024
Artificial Intelligence for Breast Ultrasound: AJR Expert Panel Narrative ReviewManisha Bahl, Jung Min Chang, Lisa A Mullen, et al.Journal of Digital Imaging|November 28, 2018
Beyond Human Perception: Sexual Dimorphism in Hand and Wrist Radiographs Is Discernible by a Deep Learning ModelSehyo Yune, Hyunkwang Lee, Myeongchan Kim, et al.Radiology|December 21, 2013
How to perform parathyroid 4D CT: tips and traps for technique and interpretationJenny K Hoang, Won-kyung Sung, Manisha Bahl, et al.Annals of Surgical Oncology|August 8, 2015
Evaluation of Pathologic Nipple Discharge: What is the Added Diagnostic Value of MRI?Manisha Bahl, Jay A Baker, Rachel A Greenup, et al.Academic Radiology|November 9, 2019
Ductal Carcinoma In Situ (DCIS) at Breast MRI: Predictors of Upgrade to Invasive CarcinomaLeslie R Lamb, Constance D Lehman, Tawakalitu O Oseni, et al.Radiology|April 3, 2019
Digital 2D versus Tomosynthesis Screening Mammography among Women Aged 65 and Older in the United StatesManisha Bahl, Niveditha Pinnamaneni, Sarah Mercaldo, et al.Radiology. Artificial Intelligence|May 3, 2021
Urinary Stone Detection on CT Images Using Deep Convolutional Neural Networks: Evaluation of Model Performance and GeneralizationAnushri Parakh, Hyunkwang Lee, Jeong Hyun Lee, et al.Physics in Medicine and Biology|October 26, 2011
A decomposition-based CT reconstruction formulation for reducing blooming artifactsSynho Do, W Clem Karl, Zhuangli Liang, et al.Pageof 15