Identifying Loose Connective and Muscle Tissues on Histology Images

  • Claudia Mazo
  • Maria Trujillo
  • Liliana Salazar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8259)


Histology images are used to identify biological structures present in living organisms — cells, tissues, and organs — correctly. The structure of tissues varies according to the type and purpose of the tissue. Automatic identification of tissues is an open problem in image processing. In this paper, the identification of loose connective and muscle tissues based on morphological tissue information is presented.

Image identification is commonly evaluated in isolation. This is done either by eye or via some other quality measure. Expert criteria — by eye — are used to evaluate the identification results. Experimental results show that the proposed approach yields results close to the real results, according to expert opinion.


Muscle Tissue Automatic Segmentation Structure Tensor Morphological Operation Loose Connective Tissue 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Claudia Mazo
    • 1
  • Maria Trujillo
    • 1
  • Liliana Salazar
    • 2
  1. 1.School of Computer and Systems EngineeringUniversidad del ValleColombia
  2. 2.Department of MorphologyUniversidad del ValleColombia

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