Efficient hierarchical layered graph approach for multi-region segmentation

@inproceedings{Leon2019EfficientHL,
  title={Efficient hierarchical layered graph approach for multi-region segmentation},
  author={Leissi Margarita Casta{\~n}eda Leon},
  year={2019}
}
Leon, Leissi M. C. Efficient Hierarchical Layered Graph Approach for MultiRegion Segmentation. 78 f. Tese (Doutorado) Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo, 2019. Image segmentation refers to the process of partitioning an image into meaningful regions of interest (objects) by assigning distinct labels to their composing pixels. Images are usually composed of multiple objects with distinctive features, thus requiring distinct highlevel priors for their… CONTINUE READING

References

Publications referenced by this paper.
SHOWING 1-10 OF 63 REFERENCES

Deep Extreme Cut: From Extreme Points to Object Segmentation

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
  • 2017
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

3d image reconstruction for comparison of algorithm database : A patientspecific anatomical and medical image database. URL https://www.ircad.fr/research/ 3d-ircadb-02

Soler et al. Luc Soler, Alexandre Hostettler, +4 authors Anne-Blandine Osswald
  • Citado na pág. xv,
  • 2012
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Star Shape Prior for Graph-Cut Image Segmentation

  • ECCV
  • 2008
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Learned Watershed: End-to-End Learning of Seeded Segmentation

  • 2017 IEEE International Conference on Computer Vision (ICCV)
  • 2017
VIEW 3 EXCERPTS
HIGHLY INFLUENTIAL

Extensions of the hierarchical graph approach in multi-region segmentation

  • Women in Computer Vision Workshop @ Computer Vision and Pattern Recognition (CVPR)
  • 2019

A hierarchical layered graph approach for multi-label segmentation in 2d medical images

  • Citado na pág
  • 2018