Reconstruction of difference in sequential CT studies using penalized likelihood estimation

A. Pourmorteza, H. Dang, Jeff Siewerdsen, Joseph Webster Stayman

Research output: Contribution to journalArticle

Abstract

Characterization of anatomical change and other differences is important in sequential computed tomography (CT) imaging, where a high-fidelity patient-specific prior image is typically present, but is not used, in the reconstruction of subsequent anatomical states. Here, we introduce a penalized likelihood (PL) method called reconstruction of difference (RoD) to directly reconstruct a difference image volume using both the current projection data and the (unregistered) prior image integrated into the forward model for the measurement data. The algorithm utilizes an alternating minimization to find both the registration and reconstruction estimates. This formulation allows direct control over the image properties of the difference image, permitting regularization strategies that inhibit noise and structural differences due to inconsistencies between the prior image and the current data. Additionally, if the change is known to be local, RoD allows local acquisition and reconstruction, as opposed to traditional model-based approaches that require a full support field of view (or other modifications). We compared the performance of RoD to a standard PL algorithm, in simulation studies and using test-bench cone-beam CT data. The performances of local and global RoD approaches were similar, with local RoD providing a significant computational speedup. In comparison across a range of data with differing fidelity, the local RoD approach consistently showed lower error (with respect to a truth image) than PL in both noisy data and sparsely sampled projection scenarios. In a study of the prior image registration performance of RoD, a clinically reasonable capture ranges were demonstrated. Lastly, the registration algorithm had a broad capture range and the error for reconstruction of CT data was 35% and 20% less than filtered back-projection for RoD and PL, respectively. The RoD has potential for delivering high-quality difference images in a range of sequential clinical scenarios including image-guided surgeries and treatments where accurate and quantitative assessments of anatomical change is desired.

Original languageEnglish (US)
Article number1986
Pages (from-to)1986-2002
Number of pages17
JournalPhysics in Medicine and Biology
Volume61
Issue number5
DOIs
StatePublished - Feb 19 2016

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Tomography
Computer-Assisted Surgery
Cone-Beam Computed Tomography
Noise
Therapeutics

Keywords

  • computed tomography
  • cone-beam CT
  • image-guided radiotherapy
  • model-based image reconstruction
  • penalized likelihood estimation
  • prior image-based reconstruction
  • statistical image reconstruction

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology

Cite this

Reconstruction of difference in sequential CT studies using penalized likelihood estimation. / Pourmorteza, A.; Dang, H.; Siewerdsen, Jeff; Stayman, Joseph Webster.

In: Physics in Medicine and Biology, Vol. 61, No. 5, 1986, 19.02.2016, p. 1986-2002.

Research output: Contribution to journalArticle

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