Computer-Aided Diagnosis for Lung CT Using Artificial Life Models

  • Authors:
  • Sorin Cristian Cheran;Gianfranco Gargano

  • Affiliations:
  • Istituto Nazionale di Fisica Nucleare, Universita degli Studi di Torino and Associazione Sviluppo Piemonte;Istituto Nazionale di Fisica Nucleare and Univerita degli Studi di Bari

  • Venue:
  • SYNASC '05 Proceedings of the Seventh International Symposium on Symbolic and Numeric Algorithms for Scientific Computing
  • Year:
  • 2005

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Abstract

With the present paper we introduce a new Computer Assisted Detection method for Lung Cancer from CT images. The algorithm is based on different algorithms like: 3D Region Growing, Active Contour And Shape Models, Centre of Maximal Balls but we can say that at the core of our approach are the Biological Models of ants also known as Artificial Life models. In the first step of the algorithm the images are undergoing a 3D region growing for identifying the ribs cage. Once the ribcage identified an Active contour is used in order to build a confined area for the incoming ants that are deployed to make clean and accurate reconstruction of the bronchial and vascular tree. Next the branches of the newly reconstructed trees are checked to see whether they include nodules or not by using Active Shape Models and to also to see if there are any nodules attached to the pleura of the lungs.(Centre of Maximal Balls). The next step is to remove the trees in order to provide a cleaner algorithm for localizing the nodules which is achieved by applying snakes and dot enhancement algorithms.