DeepQSM - Using Deep Learning to Solve the Dipole Inversion for MRI Susceptibility Mapping

By Kasper Gade Bøtker Rasmussen, Mads Kristensen, Rasmus Guldhammer Blendal, Lasse Riis Østergaard, Maciej Plocharski, Kieran O’Brien, C. Langkammer, Andrew L. Janke, Markus Barth, S. Bollmann. 2018

19 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. John M. Pauly
2. Jaeyeon Yoon
3. Enhao Gong
4. Berkin Bilgic
5. Kawin Setsompop
6. Greg Zaharchuk
7. I. Chatnuntawech
8. Jingyu Ko

Citations in the corpus

• Quantitative susceptibility mapping using deep neural network: QSMnet (2018, background): “Recently, there was a proposal of using deep neural network for QSM, trained by simulated data only (Rasmussen et al., 2018).”