Design AND DEVELOPMENT OF EFFICIENT FRAMEWORK FOR MEDICAL IMAGE RECONSTRUCTION

Abstract

Computed Tomography (CT) is an effective and indispensable imaging tool for medical image reconstruction application. It comprises positron emission to mography (PET) and single photon emission computed tomography (SPECT). It provides functional and anatomical information about physiological processes. The goal of CT is to reconstruct the distribution of the radio-isotopes in the body by measuring the emitted photons. Tomographic image reconstruction using statistical methods (e.g. MLEM, MRP, OSEM etc.) can improve the image quality over the conventional filtered back projection (FBP) method. Statistical Iterative Reconstruction (SIR) method offers many advantages like incorporating physical effects and physical constraints, modeling of complex imaging geometries, appropriate noise models, imaging at lower X-ray doses etc.