Principles and applications of balanced SSFP techniques

By K. Scheffler, S. Lehnhardt. European Radiology, 2003

734 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/1d0833f34153fc1fc19e8f0131500c8188189a0d

How researchers see this paper

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

In Biomedical Engineering

1. Klaus Hermann Maier-Hein
2. Pierre-Marc Jodoin
3. P. Heng
4. Xavier Pennec
5. Xin Yang
6. Fabian Isensee

In Radiology, Nuclear Medicine and Imaging

1. Arvid Lundervold
2. Vikas Gulani
3. Nicole Seiberlich
4. Fabian Isensee
5. Klaus Hermann Maier-Hein
6. Oscar Camara
7. Mark A. Griswold
8. P. Heng

Citations in the corpus

• A Framework for the Generation of Realistic Synthetic Cardiac Ultrasound and Magnetic Resonance Imaging Sequences From the Same Virtual Patients (2018, positive): “Cardiac cine MR images were acquired using the balanced steady state free precession (bSSFP) MR sequence [34].”
• Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved? (2018, background): “conventional SSFP sequence in breath hold with a retrospective or prospective gating [39].”
• Magnetic Resonance Fingerprinting (2013, positive): “Since both MRF and DESPOT2 are based on a bSSFP sequence, which is known to be sensitive to field inhomogeneities 30,37 , Supplementary Figure 2 compares the T 2 maps acquired from MRF and DESPOT2 from an in vivo scan.”