A level set approach for shape-driven segmentation and tracking of the left ventricle

By Nikos Paragios. IEEE Transactions on Medical Imaging, 2003

380 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/7203da2382f826ba7fcca6591a2d159d3180a91a

How researchers see this paper

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

In Computer Vision and Pattern Recognition

1. Martin Burger
2. Stanley J. Osher
3. Ronald M. Summers
4. C. Chui
5. Bing Nan Li
6. Sim Heng Ong
7. Stephen K. Y. Chang
8. Shijun Wang

In Radiology, Nuclear Medicine and Imaging

1. Martin Burger
2. Stanley J. Osher
3. Ronald M. Summers
4. Shijun Wang

Citations in the corpus

• Integrating spatial fuzzy clustering with level set methods for automated medical image segmentation (2011, background): “It is appropriate to refer the work presented in this paper to those incorporating prior knowledge into deformable models [10,11,13,21].”
• Machine Learning and Radiology (2012, methodology): “…used in medical image segmentation, such as brain (Baillard et al., 2001; Ciofolo and Barillot, 2005; Yang et al., 2003), heart (Lin et al., 2003; Paragios, 2003; Yang et al., 2003), liver (Lee et al., 2007; Smeets et al., 2010), and colon (Franaszek et al., 2006; Konukoglu et al., 2007; Uitert…”
• A survey on level set methods for inverse problems and optimal design (2005, methodology): “The segmentation of medical images by level set methods has been investigated by several authors [50, 75, 94, 111, 139].”