Research Article Open Access

A NOVEL APPROACH TO DETECT FISSURES IN LUNG CT IMAGES USING MARKER-BASED WATERSHED TRANSFORMATION

K. Devaki1 and V. Murali Bhaskaran1
  • 1 , India

Abstract

Detection and segmentation of fissures is useful in the clinical interpretation of CT lung images to diagnose the presence of pathologies in the human lungs. A new automated method based on marker-based watershed transformation has been proposed to segment the fissures considering its unique structure as a long connected component. Marker based watershed transformation is applied and morphological operations are employed to specify the internal and external markers. The smaller regions in the resulting image are removed by a novel procedure called Small Segment Removal Algorithm (SSRA) to segment the fissures alone. The performance of the method is validated by experimenting with 6 CT image sets. An expert radiologist observation is used as reference to assess the performance. A promising accuracy of 96.61% is shown with the rms error in the range of 0.877±0.224 mm for the left oblique fissure and 0.803±0.262 mm for the right oblique fissure.

Journal of Computer Science
Volume 10 No. 6, 2014, 896-905

DOI: https://doi.org/10.3844/jcssp.2014.896.905

Submitted On: 19 August 2013 Published On: 25 January 2014

How to Cite: Devaki, K. & Bhaskaran, V. M. (2014). A NOVEL APPROACH TO DETECT FISSURES IN LUNG CT IMAGES USING MARKER-BASED WATERSHED TRANSFORMATION. Journal of Computer Science, 10(6), 896-905. https://doi.org/10.3844/jcssp.2014.896.905

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Keywords

  • Lung CT Image
  • Segmentation
  • Detection
  • Fissures
  • Marker Based Watershed