The possibility to significantly reduce the X-ray radiation dose and shorten the scanning time is particularly appealing, especially for the medical imaging community. Region-of-interest Computed Tomography (ROI CT) has this potential and, for this reason, is currently receiving increasing attention. Due to the truncation of projection images, ROI CT is a rather challenging problem. Indeed, the ROI reconstruction problem is severely ill-posed in general and naive local reconstruction algorithms tend to be very unstable. To obtain a stable and reliable reconstruction, under suitable noise circumstances, we formulate the ROI CT problem as a convex optimization problem with a regularization term based on shearlets, and possibly nonsmooth. For the solution, we propose and analyze an iterative approach based on the variable metric inexact line-search algorithm (VMILA). The reconstruction performance of VMILA is compared against different regularization conditions, in the case of fan-beam CT simulated data. The numerical tests show that our approach is insensitive to the location of the ROI and remains very stable also when the ROI size is rather small.

The ROI CT problem: a shearlet-based regularization approach / Bubba, TATIANA ALESSANDRA; Porta, Federica; Zanghirati, Gaetano; Bonettini, Silvia. - In: JOURNAL OF PHYSICS. CONFERENCE SERIES. - ISSN 1742-6588. - 756:1(2016). (Intervento presentato al convegno 6th International Workshop on New Computational Methods for Inverse Problems tenutosi a Cachan nel 20 maggio 2016) [10.1088/1742-6596/756/1/012009].

The ROI CT problem: a shearlet-based regularization approach

BUBBA, TATIANA ALESSANDRA;PORTA, FEDERICA;BONETTINI, Silvia
2016

Abstract

The possibility to significantly reduce the X-ray radiation dose and shorten the scanning time is particularly appealing, especially for the medical imaging community. Region-of-interest Computed Tomography (ROI CT) has this potential and, for this reason, is currently receiving increasing attention. Due to the truncation of projection images, ROI CT is a rather challenging problem. Indeed, the ROI reconstruction problem is severely ill-posed in general and naive local reconstruction algorithms tend to be very unstable. To obtain a stable and reliable reconstruction, under suitable noise circumstances, we formulate the ROI CT problem as a convex optimization problem with a regularization term based on shearlets, and possibly nonsmooth. For the solution, we propose and analyze an iterative approach based on the variable metric inexact line-search algorithm (VMILA). The reconstruction performance of VMILA is compared against different regularization conditions, in the case of fan-beam CT simulated data. The numerical tests show that our approach is insensitive to the location of the ROI and remains very stable also when the ROI size is rather small.
2016
6th International Workshop on New Computational Methods for Inverse Problems
Cachan
20 maggio 2016
756
Bubba, TATIANA ALESSANDRA; Porta, Federica; Zanghirati, Gaetano; Bonettini, Silvia
The ROI CT problem: a shearlet-based regularization approach / Bubba, TATIANA ALESSANDRA; Porta, Federica; Zanghirati, Gaetano; Bonettini, Silvia. - In: JOURNAL OF PHYSICS. CONFERENCE SERIES. - ISSN 1742-6588. - 756:1(2016). (Intervento presentato al convegno 6th International Workshop on New Computational Methods for Inverse Problems tenutosi a Cachan nel 20 maggio 2016) [10.1088/1742-6596/756/1/012009].
File in questo prodotto:
File Dimensione Formato  
Bubba_2016_J._Phys. _Conf._Ser._756_012009.pdf

Open access

Tipologia: Versione pubblicata dall'editore
Dimensione 1.3 MB
Formato Adobe PDF
1.3 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1146895
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 4
social impact