Characterization of statistical prior image constrained compressed sensing (PICCS): II. Application to dose reduction

Purpose: The ionizing radiation imparted to patients during computed tomography exams is raising concerns. This paper studies the performance of a scheme called dose reduction using prior image constrained compressed sensing (DR-PICCS). The purpose of this study is to characterize the effects of a s...

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Veröffentlicht in:	Medical physics (Lancaster) Jg. 40; H. 2; S. 021902 - n/a
Hauptverfasser:	Lauzier, Pascal Thériault, Chen, Guang-Hong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States American Association of Physicists in Medicine 01.02.2013
Schlagworte:	60 APPLIED LIFE SCIENCES Algorithms Animals ANISOTROPY CAT SCANNING compressed sensing Computed tomography Computerised tomographs computerised tomography COMPUTERIZED SIMULATION Contrast CT dose reduction data compression DIFFUSION Digital computing or data processing equipment or methods, specially adapted for specific applications DOSES EVALUATION FILTERS image coding Image coding, e.g. from bit‐mapped to non bit‐mapped Image data processing or generation, in general image denoising Image enhancement or restoration, e.g. from bit‐mapped to bit‐mapped creating a similar image IMAGE PROCESSING Image Processing, Computer-Assisted - methods image quality evaluation image reconstruction IN VIVO Medical image noise medical image processing Medical image reconstruction Medical image spatial resolution Medical imaging Methods or arrangements for processing data by operating upon the order or content of the data handled Noise optical transfer function PATIENTS PHANTOMS Radiation Dosage Radiation Imaging Physics RADIOLOGY AND NUCLEAR MEDICINE Reconstruction Signal-To-Noise Ratio SPATIAL DISTRIBUTION SPATIAL RESOLUTION statistical image reconstruction Statistical model calculations STATISTICAL MODELS Statistics as Topic Tomography, X-Ray Computed - methods X-RAY DETECTION X‐ray imaging computed tomography CT dose reduction image quality evaluation compressed sensing statistical image reconstruction
ISSN:	0094-2405, 2473-4209, 2473-4209, 0094-2405
Online-Zugang:	Volltext
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