A binary level set model and some applications to Mumford-Shah image segmentation

By Johan Lie, Ola Marius Lysaker, Xuecheng Tai. IEEE Transactions on Image Processing, 2006

399 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Materials Chemistry, Mechanics of Materials

View Paper: https://www.semanticscholar.org/paper/b3ff36b6db348097b8724cd49b69d0f8d558bf0f

How researchers see this paper

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

In Computational Theory and Mathematics

1. Hongwei Li
2. Huihui Song
3. Kaihua Zhang
4. Lei Zhang
5. Xuecheng Tai

In Materials Chemistry

1. Hongwei Li
2. Huihui Song
3. Kaihua Zhang
4. Lei Zhang
5. Xuecheng Tai

In Mechanics of Materials

1. Hongwei Li
2. Huihui Song
3. Kaihua Zhang
4. Lei Zhang
5. Xuecheng Tai

Citations in the corpus

• Active contours driven by local image fitting energy (2010, methodology): “Generally speaking, the existing ACM methods can be classified into two types: edge-based models [1–4,6,9,14,19,20,23] and region-based models [5,7,8,10,11,16–18,21].”
• A piecewise constant level set method for elliptic inverse problems (2007, methodology): “The piecewise constant level set methods, proposed in [18,20,19], are alternatives to the level set idea of [25].”
• Improved Automatic Detection and Segmentation of Cell Nuclei in Histopathology Images (2010, methodology): “More advanced techniques are based on graphcuts [15] and level set [36] algorithms, but they require good”
• Wound intensity correction and segmentation with convolutional neural networks (2017, background): “In general, ACMs can be divided into two categories: edge-based [7, 8] and region-based [9, 10].”