SIMULATION OF POSITRON EMISSION TOMOGRAPHY FOR LUNG CANCER ANALYSIS

Hashmathunnisa Begum, Ruksar Fatima, Feroza .D.Mirajkar

Abstract: Geometric models of human body organs are obtained from imaging techniques like computed tomography (CT) and magnetic resonance image (MRI) A new technique is introduced is Positron Emission Tomography (PET) image analysis which useful and versatile to obtain accurate geometric models that can be used in several clinical cases to obtain relevant quantitative and qualitative information. one of the major use PET image is in the diagnoses of tumors. Presently simulation programs such as GATE (Geant4 Application for Tomographic Emission) exist, but they are complicated and more time consuming. This work proposes a new method to simulate the PET image of the Lungs with Monte Carlo simulation in Matlab. For the simulation, a high resolution, MRI and CT based, segmented image, is used as the original image. In MRI segmentation intensity non - uniformity (INU) artefact present. Hence, Adaptive Spatial Fuzzy Center means segmentation is used. It is based on fuzzy C - means that address both INU artifact and local spatial continuity.

Keywords: Lung Cancer, CT, MRI, membership values, clusters, fuzziness factor

DOI: https://doi.org/10.15623/ijret.2016.0533013