A computer based model for lung cancer analysis
In this paper, we have presented an innovative methodology to convey connection between physical and mechanical properties of lung tissue in some lung cancer diseases. It is proposed in this method to combine computed tomography (CT) medical images, image processing and Finite Element (FE) technique to grasp the patient lung tissue response under gradual stages of lung cancer. Finite Element models based on lung CT images of different patients are used to analyse the real behaviour of lung tissue and detect the difference between mechanical parameters in both normal and pathologic cases. Results show that normal lungs display distinct superiority in strength, and expansion properties. It is also notable that we have present new mechanical parameters to clearly describe the evolution of different patients lung cancers cases. Investigating lung cancer using such techniques is very promising to enhances data monitoring towards the development of automated diagnosis systems.
Keywords: Computed Tomography, Lung cancer, Image processing, Finite Element Analysis.
Download Full-Text
ABOUT THE AUTHORS
Fatma Ayari
she is Graduate Research Assistant of Electrical engineering. She is a PhD student in Electrical Engineering at the National School of Engineering, Tunisia. She teaches undergraduate courses in Programming Mathematics and Informatics. She’s research areas of interest include experimental and computational signal processing, neural networks and automatics. She has published in journals and proceeding conferences as IEEE proceedings.
Mekki Ksouri
he is Professor in the Department of Electrical and Computer Engineering automatics and Electrical engineering at the National School of Engineers of Tunis Tunisia. His research interests include distributed computing, neural networks, fuzzy systems, genetic and ellipsoid algorithms bioinformatics and biomimetic and bio-Inspired Computing Machines, author of scientific books. He has published a great number of scientific papers published in various IEEE and other international journals. His recent research has been supported by many international organizations, INRIA, AUF
Ali Alouani
Professor in the Department of Electrical and Computer Engineering Tennessee Technological University. He developed and taught many undergraduate and graduate courses in the Systems and Signals areas. Till date he has published in more than 120 technical journal and conference papers. He holds 4 patents.
Fatma Ayari
she is Graduate Research Assistant of Electrical engineering. She is a PhD student in Electrical Engineering at the National School of Engineering, Tunisia. She teaches undergraduate courses in Programming Mathematics and Informatics. She’s research areas of interest include experimental and computational signal processing, neural networks and automatics. She has published in journals and proceeding conferences as IEEE proceedings.
Mekki Ksouri
he is Professor in the Department of Electrical and Computer Engineering automatics and Electrical engineering at the National School of Engineers of Tunis Tunisia. His research interests include distributed computing, neural networks, fuzzy systems, genetic and ellipsoid algorithms bioinformatics and biomimetic and bio-Inspired Computing Machines, author of scientific books. He has published a great number of scientific papers published in various IEEE and other international journals. His recent research has been supported by many international organizations, INRIA, AUF
Ali Alouani
Professor in the Department of Electrical and Computer Engineering Tennessee Technological University. He developed and taught many undergraduate and graduate courses in the Systems and Signals areas. Till date he has published in more than 120 technical journal and conference papers. He holds 4 patents.