742 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- New York UniversityUS36 papers
- Center for Advanced Imaging Innovation and ResearchUS6 papers
- Courant Institute of Mathematical SciencesUS6 papers
- Harvard UniversityUS5 papers
- Massachusetts General HospitalUS4 papers
- CEA Paris-SaclayFR3 papers
- Centre Inria de SaclayFR3 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR3 papers
- Flatiron Institute3 papers
- The University of Texas at AustinUS3 papers
- Université Paris-SaclayFR3 papers
6 papers · 1 filter
High Impedance Detector Arrays for Magnetic Resonance
Bei Zhang, Daniel K. Sodickson, Martijn A. Cloos
Resonant inductive coupling is commonly seen as an undesired fundamental phenomenon emergent in densely packed resonant structures, such as nuclear magnetic resonance phased array…
Utility of General and Specific Word Embeddings for Classifying Translational Stages of Research
Vincent Major, Alisa Surkis, Yindalon Aphinyanaphongs
Conventional text classification models make a bag-of-words assumption reducing text into word occurrence counts per document. Recent algorithms such as word2vec are capable of lea…
Learning a Variational Network for Reconstruction of Accelerated MRI Data
Kerstin Hammernik, Teresa Klatzer, Erich Kobler +4
Purpose: To allow fast and high-quality reconstruction of clinical accelerated multi-coil MR data by learning a variational network that combines the mathematical structure of vari…
Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks
Cem M. Deniz, Siyuan Xiang, Spencer Hallyburton +5
Magnetic resonance imaging (MRI) has been proposed as a complimentary method to measure bone quality and assess fracture risk. However, manual segmentation of MR images of bone is…
Why do similarity matching objectives lead to Hebbian/anti-Hebbian networks?
Cengiz Pehlevan, Anirvan Sengupta, Dmitri B. Chklovskii
Modeling self-organization of neural networks for unsupervised learning using Hebbian and anti-Hebbian plasticity has a long history in neuroscience. Yet, derivations of single-lay…
Optimized Quantification of Spin Relaxation Times in the Hybrid State
Jakob Assländer, Riccardo Lattanzi, Daniel K Sodickson +1
Purpose: The analysis of optimized spin ensemble trajectories for relaxometry in the hybrid state. Methods: First, we constructed visual representations to elucidate the differenti…