Reconstruction of fetal brain MRI with intensity matching and complete outlier removal
By Maria Murgasova, Gerardine Quaghebeur, Mary A. Rutherford, Joseph V. Hajnal, Julia A. Schnabel. Medical Image Anal., 2012
420 citations recorded by the source corpus.
Graphical abstract Highlights ► A new method for reconstruction of 3D fetal brain MRI from 2D slices is proposed. ► The super-resolution reconstruction is interleaved with motion correction. ► Corrupted or misaligned slices are automatically excluded. ► Novel intensity matching is shown to be essential for quality of reconstruction. ► Excellent results for clinical and optimized data.
Subfields: Pediatrics, Perinatology and Child Health, Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/8cef20ab69e1b1c85696f4a01358ef6c1be43552
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Pediatrics, Perinatology and Child Health
- Daniel Rueckert
- Antonios Makropoulos
- Nikos Paragios
- Mark Jenkinson
- Stephen M. Smith
- Serena J. Counsell
- Enzo Ferrante
In Radiology, Nuclear Medicine and Imaging
- Matthew F. Glasser
- Stephen M. Smith
- Timothy S. Coalson
- Daniel Rueckert
- Mark Jenkinson
- Emma Claire Robinson
- D. V. Van Essen
- Antonios Makropoulos
Citations in the corpus
- The Developing Human Connectome Project: a Minimal Processing Pipeline for Neonatal Cortical Surface Reconstruction (2017, methodology): “The processing steps are as follows: 1) acquisition and reconstruction of T1 and T2 images (Cordero-Grande et al., 2017; Hughes et al., 2016; Kuklisova-Murgasova et al., 2012); 2) tissue segmentation and regional labelling (Makropoulos et al.”
- Slice-to-volume medical image registration: a survey (2017, methodology): “In this case, reconstruction error measured through intensity differences (usually the root mean square differences or RMSD) or signal-to-noise ratio (SNR) indicators between estimated and ground-truth volumes were used (Zarow et al., 2004; Noble et al., 2005; Chandler et al., 2006; Jiang et al., 20”
- Multimodal Surface Matching with Higher-Order Smoothness Constraints☆ (2017, methodology): “Overlapping slices (resolution (mm) 0.8×0.8×1.6) were acquired to give final image resolution voxels 0.8 × 0.8 × 0.8mm3 after motion corrected reconstruction, combining Cordero-Grande et al. (2016); Kuklisova-Murgasova et al. (2012).”
- A review on automatic fetal and neonatal brain MRI segmentation (2017, positive): “Slice-to-volume (SVR) techniques (Rousseau et al., 2006; Jiang et al., 2007; Gholipour et al., 2010; Kuklisova-Murgasova et al., 2012; Cordero-Grande et al., 2016) usually perform this correction in two iterative steps: a) 3D reconstruction from the 2D slices and b) re-alignment of the 2D slices to…”