[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Jiao et al., 2008 - Google Patents

Multiscale noise reduction on low-dose CT sinogram by stationary wavelet transform

Jiao et al., 2008

Document ID
1302796791232582383
Author
Jiao C
Wang D
Lu H
Zhang Z
Liang J
Publication year
Publication venue
2008 IEEE Nuclear Science Symposium Conference Record

External Links

Snippet

Low-dose protocol for computed tomography (CT) scans has been gradually used in clinics to lower the radiation exposure for mass screening. However, the high noise during data acquisition (and therefore degraded image quality) impairs diagnostic accuracy. This work …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • 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
    • G06T5/001—Image restoration
    • G06T5/002—Denoising; Smoothing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20048—Transform domain processing
    • G06T2207/20056—Discrete and fast Fourier transform, [DFT, FFT]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20048—Transform domain processing
    • G06T2207/20064—Wavelet transform [DWT]
    • 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
    • G06T5/001—Image restoration
    • G06T5/003—Deblurring; Sharpening
    • G06T5/004—Unsharp masking
    • 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
    • G06T2207/10072—Tomographic images
    • G06T2207/10084—Hybrid tomography; Concurrent acquisition with multiple different tomographic modalities
    • 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
    • G06T2207/10072—Tomographic images
    • G06T2207/10104—Positron emission tomography [PET]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20172—Image enhancement details
    • G06T2207/20182—Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
    • 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
    • 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
    • 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
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10116—X-ray image
    • 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
    • G06T5/20—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image by the use of local operators

Similar Documents

Publication Publication Date Title
Hu et al. Artifact correction in low‐dose dental CT imaging using Wasserstein generative adversarial networks
Wang et al. Multiscale penalized weighted least-squares sinogram restoration for low-dose X-ray computed tomography
CN108961237B (en) Low-dose CT image decomposition method based on convolutional neural network
CN112258415B (en) Chest X-ray film super-resolution and denoising method based on generation countermeasure network
CN109785243B (en) Denoising method and computer based on unregistered low-dose CT of countermeasure generation network
Naranjo et al. Metal artifact reduction in dental CT images using polar mathematical morphology
Zhang et al. Statistical image reconstruction for low-dose CT using nonlocal means-based regularization. Part II: An adaptive approach
CN110223255B (en) Low-dose CT image denoising and recursion method based on residual error coding and decoding network
Raj et al. Denoising of medical images using dual tree complex wavelet transform
WO2014172421A1 (en) Iterative reconstruction for x-ray computed tomography using prior-image induced nonlocal regularization
Cui et al. Learning-based artifact removal via image decomposition for low-dose CT image processing
Koyuncu et al. Elimination of white Gaussian noise in arterial phase CT images to bring adrenal tumours into the forefront
Liu et al. Noise reduction for low-dose X-ray CT based on fuzzy logical in stationary wavelet domain
Jiao et al. Multiscale noise reduction on low-dose CT sinogram by stationary wavelet transform
Raj et al. Denoising of magnetic resonance and x-ray images using variance stabilization and patch based algorithms
Jeong et al. Reduction of artifacts due to multiple metallic objects in computed tomography
Kadam et al. An improved image denoising using spatial adaptive mask filter for medical images
Sakata et al. Noise reduction and contrast enhancement for small-dose X-ray images in wavelet domain
Shih et al. Noise reduction of low-dose computed tomography using the multi-resolution total variation minimization algorithm
Kumar et al. Edge preservation based CT image denoising using wavelet and curvelet transforms
Ding et al. Efficient scheme of low-dose CT reconstruction using TV minimization with an adaptive stopping strategy and sparse dictionary learning for post-processing
Mohan et al. A novel method of medical image denoising using bilateral and NLM filtering
Wang et al. Magnetic resonance image restoration via dictionary learning under spatially adaptive constraints
Li et al. Denoising Algorithm Combining Cone Beam CT Projection Data with Reconstructed Image
Zhang et al. Medical image denoising