Active shape model segmentation with optimal features

By B. van Ginneken, Alejandro F Frangi, Joes Staal, B. T. H. Romeny, Max A. Viergever. IEEE Transactions on Medical Imaging, 2002

606 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/99840ed7cc49c379273099b57bf58f55f5274e64

How researchers see this paper

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

In Artificial Intelligence

1. Thomas S. Huang
2. Zhe L. Lin
3. Lubomir D. Bourdev
4. Zhuowen Tu
5. Vuong Le
6. Stefan Jaeger
7. George R. Thoma
8. Jonathan Brandt

In Computer Vision and Pattern Recognition

1. Luc Van Gool
2. Dacheng Tao
3. Ming-Hsuan Yang
4. Jitendra Malik
5. Xiaogang Wang
6. Chen Change Loy
7. Trevor Darrell
8. Andrea Vedaldi

Citations in the corpus

• Lung Segmentation in Chest Radiographs Using Anatomical Atlases With Nonrigid Registration (2013, positive): “Active shape models (ASM) [21] and active appearance models (AAM) [22] have been successfully applied to lung region segmentation [23], [24], [15], [25]–[27].”
• Interactive Facial Feature Localization (2012, methodology): “For example, [8] employs mixtures of Gaussians for representing the shape, [9] uses Kernel PCA and SVM, and models nonlinear shape changes by 3D rotation, [10] apply robust least squares algorithms to match the shapes to observations, [11] uses more robust texture descriptors to replace the 1D profi”
• Efficient and generalizable statistical models of shape and appearance for analysis of cardiac MRI (2008, methodology): “We also experimented with the method described in van Ginneken et al. (2002).”
• A framework for evaluating image segmentation algorithms (2006, methodology): “Such a choice has been utilized in the past for TPVF (for example in [25]) and for TPVF, FPVF, and FNVF [26,27].”
• Robust Brain Extraction Across Datasets and Comparison With Publicly Available Methods (2011, methodology): “For example, Gaussian shape models are used in conjunction with probabilistic boo sting trees in [19] and with ak nearest neighbor classifier in [20] and [21].”
• A review of algorithms for medical image segmentation and their applications to the female pelvic cavity (2010, methodology): “ASM and AAM have been applied widely in medical image segmentation and registration (Cootes et al. 1994; Ginneken et al. 2002; Beichel et al. 2005; Vasconcelos and Tavares 2008).”