© The Author(s) CTmod- Mathematical Foundations

Institutionen för medicin och hälsa Avdelningen för radiologiska vetenskaper Medicinsk radiofysi

© The Author(s) Validation of the CTmod toolkit

Institutionen för medicin och hälsa Avdelningen för radiologiska vetenskape

Institutionen för medicin och hälsa Avdelningen för radiologiska vetenskaper

Hälsouniversitetet Calculation of the energy absorption efficiency function of selected detector arrays using the MCNP cod

N.B.: When citing this work, cite the original article. Original Publication:

The potential of dual-energy computed tomography for quantitative decomposition of soft tissues to water, protein and lipid in brachytherap

Iterative Reconstruction for Quantitative Tissue Decomposition in Dual-Energy CT

Abstract. Quantitative tissue classification using dual-energy CT has the potential to improve accuracy in radiation therapy dose planning as it provides more information about material composition of scanned objects than the currently used methods based on single-energy CT. One problem that hinders successful application of both single- and dualenergy CT is the presence of beam hardening and scatter artifacts in reconstructed data. Current pre- and post-correction methods used for image reconstruction often bias CT numbers and thus limit their applicability for quantitative tissue classification. Here we demonstrate simulation studies with a novel iterative algorithm that decomposes every soft tissue voxel into three base materials: water, protein and adipose. The results demonstrate that beam hardening artifacts can effectively be removed and accurate estimation of mass fractions of all base materials can be achieved. In the future, the algorithm may be developed further to include segmentation of soft and bone tissue and subsequent bone decomposition, extension from 2-D to 3-D and scatter correction