Texture based segmentation of epithelial layer from oral histological images

  • Muthu Rama Krishnan M
  • Choudhary A
  • Chakraborty C
 et al. 
  • 20

    Readers

    Mendeley users who have this article in their library.
  • 14

    Citations

    Citations of this article.

Abstract

The objective of this paper is to provide a texture based segmentation algorithm for better delineation of the epithelial layer from histological images in discriminating normal and oral sub-mucous fibrosis (OSF). As per literature and oral clinicians, it is established that the OSF initially originates and propagates in the epithelial layer. So, more accurate segmentation of this layer is extremely important for a clinician to make a diagnostic decision. In doing this, Gabor based texture gradient is computed in gray scale images, followed by preprocessing of the microscopic images of oral histological sections. On the other hand, the color gradients of these images are obtained in the transformed Lab color space. Finally, the watershed segmentation is extended to segment the layer based on the combination of texture and color gradients. The segmented images are compared with the ground truth images provided by the oral experts. The segmentation results depict the superiority of the texture based segmentation in comparison to the Otsu's based segmentation in terms of misclassification error. Results are shown and discussed. © 2011 Elsevier Ltd.

Author-supplied keywords

  • Oral histology
  • Quantitative microscopy
  • Texture
  • Watershed segmentation

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Authors

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free