Iterative Reconstruction for QuantitativeTissue Decomposition in Dual-Energy CT
2011 (English)In: Proceedings of the 17th Scandinavian Conference, SCIA 2011, Ystad, Sweden, May 2011., Springer Berlin/Heidelberg, 2011, 479-488 p.Conference paper (Refereed)
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.
Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2011. 479-488 p.
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 6688
Iterative reconstruction, Dual energy CT, Tissue classiﬁca
Medical and Health Sciences
IdentifiersURN: urn:nbn:se:liu:diva-75345DOI: 10.1007/978-3-642-21227-7_45ISBN: 978-3-642-21226-0 (print)ISBN: 978-3-642-21227-7 (online)OAI: oai:DiVA.org:liu-75345DiVA: diva2:506005
Proceedings 17th Scandinavian Conference on Image Analysis (SCIA) 2011, May 23-27, Ystad, Sweden