S
Sharmila Majumdar
Researcher at University of California, San Francisco
Publications - 505
Citations - 29773
Sharmila Majumdar is an academic researcher from University of California, San Francisco. The author has contributed to research in topics: Osteoarthritis & Cartilage. The author has an hindex of 88, co-authored 477 publications receiving 27074 citations. Previous affiliations of Sharmila Majumdar include University of California & Georgia Regents University.
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Three-Dimensional-Line Skeleton Graph Analysis of High-Resolution Magnetic Resonance Images: A Validation Study From 34-μm-Resolution Microcomputed Tomography
TL;DR: The aim of this work was to show the ability of the three‐dimensional‐line skeleton graph analysis (3D‐LSGA) to characterize high‐resolution MRIs of trabecular bone structure, giving an indirect characterization of the microtrabecULAR bone network.
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Assessment of trabecular bone structure using MDCT: comparison of 64- and 320-slice CT using HR-pQCT as the reference standard
Ahi Sema Issever,Thomas M. Link,Marie Kentenich,Patrik Rogalla,Andrew J. Burghardt,Galateia J. Kazakia,Sharmila Majumdar,Gerd Diederichs +7 more
TL;DR: The 64- and 320-slice MDCT systems both perform equally well in depicting trabecular bone architecture, however, because of constrained resolutions accurate derivation of trabECular bone measures is limited to only a subset of microarchitectural parameters.
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Deep Learning Predicts Total Knee Replacement from Magnetic Resonance Images.
TL;DR: A deep learning pipeline is presented that leverages MRI images and clinical and demographic information to predict total knee replacement (TKR) with AUC 0.834 ± 0.036 (p < 0.05) for patients without OA, and the biomarkers identified further the authors' understanding of OA progression and eventual TKR onset.
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Comparison of clinical semi-quantitative assessment of muscle fat infiltration with quantitative assessment using chemical shift-based water/fat separation in MR studies of the calf of post-menopausal women
Hamza Alizai,Lorenzo Nardo,Dimitrios C. Karampinos,Gabby B. Joseph,Samuel P. Yap,Thomas Baum,Roland Krug,Sharmila Majumdar,Thomas M. Link +8 more
TL;DR: Semi-quantitative grading of intramuscular fat and quantitative fat fraction were significantly correlated and both techniques had excellent reproducibility, however, the clinical grading was found to overestimate muscle fat.
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Cerebral perfusion in children: detection with dynamic contrast-enhanced T2*-weighted MR images.
TL;DR: Cerebral perfusion dynamics were assessed with dynamic contrast material-enhanced T2*-weighted magnetic resonance (MR) imaging in 33 subjects aged 3-20 years and Group A demonstrated symmetric sequential region patterns of loss of signal intensity within 10 seconds of injection.