Lung Detection and Segmentation Using Marker Watershed and Laplacian Filtering

@inproceedings{Saii2015LungDA,
  title={Lung Detection and Segmentation Using Marker Watershed and Laplacian Filtering},
  author={Mariam Mohammad Saii and Ali Mia},
  year={2015}
}
This paper proposes a new speed approach for the segmentation of the lung images in order to detect and extract the tumor region. The approach consists of two main stages, which are the preprocessing stage, marker watershed stage and the tumor detection stage. The preprocessing consists of laplacian filtering to enhance edges and make the next stages more efficient. The marker watershed step applies the Sobel gradient function on the foreground and background markers to get the possible tumor… CONTINUE READING

References

Publications referenced by this paper.
SHOWING 1-10 OF 13 REFERENCES

Automatic lung tumor segmentation with leaks removal in follow-up CT studies

  • International Journal of Computer Assisted Radiology and Surgery
  • 2015
VIEW 1 EXCERPT

A computer based model for lung cancer

Fatma Ayari, Mekki Ksouri, Ali Alouani
  • analysis”, International Journal of Computer Science Issues,
  • 2012
VIEW 1 EXCERPT

AL-TARAWNEH, “Lung Cancer Detection Using Image Processing Techniques

S. Mokhled
  • Leonardo Electronic Journal of Practices and Technologies, Issue 20,
  • 2012
VIEW 1 EXCERPT

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