Song et al., 2018 - Google Patents
3-D MTF Estimation Using Sphere Phantoms for Cone-Beam Computed Tomography SystemsSong et al., 2018
- Document ID
- 8370707792324086591
- Author
- Song H
- Lee C
- Baek J
- Publication year
- Publication venue
- 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC)
External Links
Snippet
We propose a new method to estimate 2-D plane of 3-D modulation transfer function (MTF) of cone-beam computed tomography (CBCT) systems using sphere phantoms. Since the 2- D plane of 3-D MTF can be calculated by taking Fourier transform of 2-D projection of the 3 …
- 238000007408 cone-beam computed tomography 0 title abstract description 13
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/003—Reconstruction from projections, e.g. tomography
- G06T11/005—Specific pre-processing for tomographic reconstruction, e.g. calibration, source positioning, rebinning, scatter correction, retrospective gating
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/003—Reconstruction from projections, e.g. tomography
- G06T11/006—Inverse problem, transformation from projection-space into object-space, e.g. transform methods, back-projection, algebraic methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2211/00—Image generation
- G06T2211/40—Computed tomography
- G06T2211/424—Iterative
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2211/00—Image generation
- G06T2211/40—Computed tomography
- G06T2211/416—Exact reconstruction
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
- A61B6/02—Devices for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
- A61B6/03—Computerised tomographs
- A61B6/032—Transmission computed tomography [CT]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
- A61B6/58—Testing, adjusting or calibrating devices for radiation diagnosis
- A61B6/582—Calibration
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
- A61B6/48—Diagnostic techniques
- A61B6/482—Diagnostic techniques involving multiple energy imaging
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N23/00—Investigating or analysing materials by the use of wave or particle radiation not covered by G01N21/00 or G01N22/00, e.g. X-rays or neutrons
- G01N23/02—Investigating or analysing materials by the use of wave or particle radiation not covered by G01N21/00 or G01N22/00, e.g. X-rays or neutrons by transmitting the radiation through the material
- G01N23/04—Investigating or analysing materials by the use of wave or particle radiation not covered by G01N21/00 or G01N22/00, e.g. X-rays or neutrons by transmitting the radiation through the material and forming a picture
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US20220292646A1 (en) | System and method for image reconstruction | |
Zhu et al. | Improved compressed sensing‐based algorithm for sparse‐view CT image reconstruction | |
US6879715B2 (en) | Iterative X-ray scatter correction method and apparatus | |
CN103501702B (en) | Medical image-processing apparatus, medical image processing method | |
US7251306B2 (en) | Methods, apparatus, and software to facilitate iterative reconstruction of images | |
US8885903B2 (en) | Method and apparatus for statistical iterative reconstruction | |
US10255696B2 (en) | System and method for image reconstruction | |
US20130202080A1 (en) | System and Method for Denoising Medical Images Adaptive to Local Noise | |
Zhao et al. | Patient-specific scatter correction for flat-panel detector-based cone-beam CT imaging | |
CN101473348A (en) | Method and system for error compensation | |
Staub et al. | A digitally reconstructed radiograph algorithm calculated from first principles | |
CN112204607B (en) | Scattering correction for X-ray imaging | |
Friot et al. | Iterative tomographic reconstruction with TV prior for low-dose CBCT dental imaging | |
Lee et al. | A new method to measure directional modulation transfer function using sphere phantoms in a cone beam computed tomography system | |
Kole et al. | Evaluation of the ordered subset convex algorithm for cone-beam CT | |
Lee et al. | 3D MTF estimation using sphere phantoms for cone‐beam computed tomography systems | |
Aootaphao et al. | Experiment-based scatter correction for cone-beam computed tomography using the statistical method | |
Song et al. | 3-D MTF Estimation Using Sphere Phantoms for Cone-Beam Computed Tomography Systems | |
Rit et al. | List-mode proton CT reconstruction using their most likely paths via the finite Hilbert transform of the derivative of the backprojection | |
Thierry et al. | Hybrid simulation of scatter intensity in industrial cone-beam computed tomography | |
Lee et al. | A sphere phantom approach to measure directional modulation transfer functions for tomosynthesis imaging systems | |
Gopi et al. | Iterative computed tomography reconstruction from sparse-view data | |
Messali et al. | A quantitative comparative study of back projection, filtered back projection, gradient and bayesian reconstruction algorithms in computed tomography (ct) | |
Lee et al. | A simulation study of high-resolution x-ray computed tomography imaging using irregular sampling with a photon-counting detector | |
EP4497388A1 (en) | Determining a scatter correction |