Automatic Lung Nodule Detection Using Template Matching

  • Serhat Ozekes
  • A. Yilmaz Camurcu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4243)


We have developed a computer-aided detection system for detecting lung nodules, which generally appear as circular areas of high opacity on serial-section CT images. Our method detected the regions of interest (ROIs) using the density values of pixels in CT images and scanning the pixels in 8 directions by using various thresholds. Then to reduce the number of ROIs the amounts of change in their locations based on the upper and the lower slices were examined, and finally a nodule template based algorithm was employed to categorize the ROIs according to their morphologies. To test the system’s efficiency, we applied it to 276 normal and abnormal CT images of 12 patients with 153 nodules. The experimental results showed that using three templates with diameters 8, 14 and 20 pixels, the system achieved 91%, 94% and 95% sensitivities with 0.7, 0.98 and 1.17 false positives per image respectively.


Lung Nodule Template Match Black Pixel White Pixel Lung Nodule Detection 
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 2006

Authors and Affiliations

  • Serhat Ozekes
    • 1
  • A. Yilmaz Camurcu
    • 2
  1. 1.Istanbul Commerce UniversityIstanbulTurkey
  2. 2.Marmara University, GoztepeIstanbulTURKEY

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