Can conclusions drawn from phantom‐based image noise assessments be generalized to in vivo studies for the nonlinear model‐based iterative reconstruction method?

• Published in: Medical physics (Lancaster) Vol. 43; no. 2; pp. 687 - 695
• Main Authors: Gomez‐Cardona, Daniel, Li, Ke, Hsieh, Jiang, Lubner, Meghan G., Pickhardt, Perry J., Chen, Guang‐Hong
• Format: Journal Article
• Language: English
• Published: United States American Association of Physicists in Medicine 01.02.2016
• Subjects: Adult; Aged; Aged, 80 and over; Animals; Biological material, e.g. blood, urine; Haemocytometers; Computed tomography; Computerised tomographs; computerised tomography; Data analysis; DIAGNOSTIC IMAGING (IONIZING AND NON-IONIZING); Digital computing or data processing equipment or methods, specially adapted for specific applications; Female; General statistical methods; Germanium; Humans; Image data processing or generation, in general; Image Processing, Computer-Assisted - instrumentation; Image quality assessment; image reconstruction; iterative methods; least squares approximations; liver; Male; mAs; Medical image contrast; Medical image noise; medical image processing; Medical image reconstruction; Middle Aged; model based iterative reconstruction (MBIR); noise variance; Nonlinear Dynamics; Numerical approximation and analysis; phantoms; Phantoms, Imaging; Probability theory, stochastic processes, and statistics; radiation dose reduction; Reconstruction; regression analysis; Signal-To-Noise Ratio; Swine; Tomography, X-Ray Computed

Purpose: Phantom‐based objective image quality assessment methods are widely used in the medical physics community. For a filtered backprojection (FBP) reconstruction‐based linear or quasilinear imaging system, the use of this methodology is well justified. Many key image quality metrics acquired wi...