Zobrazeno 1 - 10
of 74
pro vyhledávání: '"Sujata V Ghate"'
Publikováno v:
Journal of Breast Imaging.
Myeloid sarcoma (MS) is a rare extramedullary solid tumor arising most often in patients with current or subsequent acute myeloid leukemia (AML). Patients of all ages may present with involvement of the skin, lymph nodes, intestinal tract, bone, and/
Autor:
Mary Scott Soo, Lucy Xiangxi Lu, E. Shelley Hwang, Connie Kim, Lars J. Grimm, Ruth Walsh, Sujata V. Ghate, Vignesh Selvakumaran, Tyler P. Litton, Rui Hou, Joseph Y. Lo, Sora C. Yoon, Jay A. Baker, Amrita Devalapalli
Publikováno v:
Acad Radiol
Rationale and Objectives The purpose of this study is to quantify breast radiologists’ performance at predicting occult invasive disease when ductal carcinoma in situ (DCIS) presents as calcifications on mammography and to identify imaging and hist
Autor:
Tyler P. Litton, Sujata V. Ghate
Publikováno v:
Radiology Case Reports
Radiology Case Reports, Vol 15, Iss 8, Pp 1194-1196 (2020)
Radiology Case Reports, Vol 15, Iss 8, Pp 1194-1196 (2020)
Axillary lymph nodes can appear abnormal on mammography due to uptake of tattoo pigment and a malignant cause must be excluded through diagnostic workup. Furthermore, tattoo pigment can mimic malignant pathology at surgery or confound appropriate sta
Publikováno v:
Journal of Breast Imaging. 1:37-42
ObjectiveThe purpose of this study was to determine the malignancy rate of solitary MRI masses with benign BI-RADS descriptors.MethodsA retrospective review was conducted of all breast MRI reports that described a mass with a final BI-RADS assessment
Autor:
Connie Kim, Maciej A. Mazurowski, Ashirbani Saha, Sujata V. Ghate, Mary Scott Soo, Sora C. Yoon, Lars J. Grimm
Publikováno v:
Journal of Magnetic Resonance Imaging. 50:456-464
BACKGROUND Preliminary work has demonstrated that background parenchymal enhancement (BPE) assessed by radiologists is predictive of future breast cancer in women undergoing high-risk screening MRI. Algorithmically assessed measures of BPE offer a mo
Autor:
Connie Kim, Lars J. Grimm, Ashirbani Saha, Maciej A. Mazurowski, Sujata V. Ghate, Mary Scott Soo, Sora C. Yoon
Publikováno v:
Academic Radiology. 26:69-75
Rationale and Objectives To determine if background parenchymal enhancement (BPE) on screening breast magnetic resonance imaging (MRI) in high-risk women correlates with future cancer. Materials and Methods All screening breast MRIs (n = 1039) in hig
Autor:
Maitray D. Patel, Sonia Gupta, Stephen I. Johnson, William D. Middleton, Eric Rubin, Alyssa R. Goldbach, Darcy J. Wolfman, Sujata V. Ghate, Marielia Gerena, Nirvikar Dahiya, Madison Kocher, Lauren Parks Golding, Phyllis Glanc, Paul Armstrong Hill, Mary C. Frates, Mindy M. Horrow, Aya Kamaya, Wui K. Chong, Jeffrey Waltz, Roya Sohaey
Publikováno v:
Journal of the American College of Radiology : JACR. 18(1 Pt)
Current descriptions of ultrasound evaluations, including use of the term "point-of-care ultrasound" (POCUS), are imprecise because they are predicated on distinctions based on the device used to obtain images, the location where the images were obta
Autor:
E. Shelley Hwang, Mary Scott Soo, Sora C. Yoon, Benjamin Neely, Terry Hyslop, Tyler P. Litton, Rui Hou, Ruth Walsh, Vignesh Selvakumaran, Connie Kim, Sujata V. Ghate, Jay A. Baker, Joseph Y. Lo, Amrita Devalapalli, Lars J. Grimm
Publikováno v:
AJR. American journal of roentgenology. 216(4)
Please see the Editorial Comment by Corinne Balleyguier discussing this article. To listen to the podcast associated with this article, please select one of the following: iTunes, Google Play, or d...
Publikováno v:
Radiographics : a review publication of the Radiological Society of North America, Inc. 40(5)
Fetal central nervous system (CNS) abnormalities are second only to cardiac malformations in their frequency of occurrence. Early and accurate diagnosis at prenatal US is therefore essential, allowing improved prenatal counseling and facilitating app
Autor:
Maciej A. Mazurowski, Ruth Walsh, Mateusz Buda, Nianyi Li, Albert Swiecicki, Sujata V. Ghate, Ashirbani Saha
Publikováno v:
Medical Imaging 2020: Computer-Aided Diagnosis.
Deep learning has achieved great success in image analysis and decision making in radiology. However, a large amount of annotated imaging data is needed to construct well-performing deep learning models. A particular challenge in the context of breas