Retrospective correction of MR intensity inhomogeneity by information minimization

By Bostjan Likar, Max A. Viergever, Franjo Pernus. IEEE Transactions on Medical Imaging, 2000

332 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/904488b9e9ec74c6a214b7048789e51a5942322f

How researchers see this paper

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

In Computational Mechanics

1. A. Ramli
2. Syamsiah Mashohor
3. M. Iqbal Bin Saripan
4. M. Balafar

In Computer Vision and Pattern Recognition

1. Adolf Pfefferbaum
2. Edith V. Sullivan
3. Natalie M. Zahr
4. A. Ramli
5. Sergi Valverde
6. Robert Marti
7. Xavier Lladó
8. Arnau Oliver

Citations in the corpus

• Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review (2017, background): “2016 [25] Intensity scaling Bias field correction ([134]) Skull stripping (BET) Tissue”
• The SRI24 Multi-Channel Atlas of Normal Adult Human Brain Structure (2009, methodology): “A separate second-order multiplicative bias field for intensity inhomogeneity correction [Likar et al., 2001] was computed from, and applied to, the SPGR image.”
• Review of brain MRI image segmentation methods (2010, methodology): “The spatial distribution of the flip angle for certain pulse sequences is estimated to obtain inhomogeneity field (Likar et al. 2001).”