Consistent and Elastic Registration of Histological Sections Using Vector-Spline Regularization
By Ignacio Arganda-Carreras, Carlos Oscar Sánchez Sorzano, Roberto Marabini, J. M. Carazo, Carlos Ortiz-de-Solorzano, Jan Kybic. CVAMIA, 2006
367 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/bf1f5154b832c9301bae23ac59abd4007abe5e38
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
- Carlos Ortiz-de-Solorzano
- Arrate Muñoz-Barrutia
- Pingkun Yan
- Thomas Martin Deserno
- Benjamin Berkels
- Kevin W. Eliceiri
- Tobias Pietzsch
- Uwe Kruger
In Computer Vision and Pattern Recognition
- Kevin W. Eliceiri
- Johannes E. Schindelin
- Curtis T. Rueden
- Stephan Preibisch
- Benjamin Schmid
- Carlos Ortiz-de-Solorzano
- Arrate Muñoz-Barrutia
- Ignacio Arganda-Carreras
Citations in the corpus
- Deep learning in medical image registration: a survey (2019, methodology): “This approach outperforms the bUnwarpJ registration technique [4] and the Elastic registration technique [105].”
- Survey of Non-Rigid Registration Tools in Medicine (2017, methodology): “The registration method is based on B-spline model to describe the deformation field and vectorspline regularization [61].”
- Fiji - an Open Source platform for biological image analysis (2012, methodology): “Relatively simple ssTEM data sets can be reconstructed using standalone plugins such as Register Virtual Stack Slices, Elastic Alignment and Montage 35 or bUnwarpJ 36 .”
- 3D reconstruction of histological sections: Application to mammary gland tissue (2010, methodology): “Therefore, we opted for combining a local correlation-based registration method with a consistent elastic registration algorithm (Arganda-Carreras et al., 2006).”