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

Jung et al., 2020 - Google Patents

Compton background elimination for in vivo X-ray fluorescence imaging of gold nanoparticles using convolutional neural network

Jung et al., 2020

Document ID
5402572418320975148
Author
Jung S
Lee J
Cho H
Kim T
Ye S
Publication year
Publication venue
IEEE Transactions on Nuclear Science

External Links

Snippet

This article reports the first application of a convolutional neural network (CNN) to in vivo X- ray fluorescence (XRF) images of gold nanoparticles (GNPs) obtained by a benchtop X-ray system to eliminate Compton-scattered photons. The XRF imaging system comprises a 2-D …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/002D [Two Dimensional] image generation
    • G06T11/003Reconstruction from projections, e.g. tomography
    • G06T11/005Specific pre-processing for tomographic reconstruction, e.g. calibration, source positioning, rebinning, scatter correction, retrospective gating
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10072Tomographic images
    • G06T2207/10084Hybrid tomography; Concurrent acquisition with multiple different tomographic modalities
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
    • A61B6/48Diagnostic techniques
    • A61B6/482Diagnostic techniques involving multiple energy imaging
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
    • A61B6/02Devices for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
    • A61B6/03Computerised tomographs
    • A61B6/032Transmission computed tomography [CT]
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0012Biomedical image inspection
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01TMEASUREMENT OF NUCLEAR OR X-RADIATION
    • G01T1/00Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
    • G01T1/29Measurement performed on radiation beams, e.g. position or section of the beam; Measurement of spatial distribution of radiation
    • G01T1/2914Measurement of spatial distribution of radiation
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
    • A61B6/50Clinical applications
    • A61B6/507Clinical applications involving determination of haemodynamic parameters, e.g. perfusion CT
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
    • A61B6/58Testing, adjusting or calibrating devices for radiation diagnosis
    • A61B6/582Calibration

Similar Documents

Publication Publication Date Title
EP3735177B1 (en) Full dose pet image estimation from low-dose pet imaging using deep learning
US11302003B2 (en) Deep learning based data-driven approach for attenuation correction of pet data
JP4414410B2 (en) Image reconstruction method
US11328391B2 (en) System and method for controlling noise in multi-energy computed tomography images based on spatio-spectral information
US12073492B2 (en) Method and system for generating attenuation map from SPECT emission data
WO2002086821A1 (en) Image processing method and image processing device
Jung et al. Compton background elimination for in vivo X-ray fluorescence imaging of gold nanoparticles using convolutional neural network
US20230059132A1 (en) System and method for deep learning for inverse problems without training data
JP7517420B2 (en) Method for generating an absorption coefficient image, nuclear medicine diagnostic device, and method for creating a trained model
Johnston et al. Temporal and spectral imaging with micro‐CT
Zimmerman et al. Experimental investigation of neural network estimator and transfer learning techniques for K‐edge spectral CT imaging
Yabe et al. Deep learning-based in vivo dose verification from proton-induced secondary-electron-bremsstrahlung images with various count level
Izadi et al. Enhanced direct joint attenuation and scatter correction of whole-body PET images via context-aware deep networks
CN116385582A (en) X-ray fluorescence CT self-absorption correction method based on deep learning
Shi et al. Reconstruction of x-ray fluorescence computed tomography from sparse-view projections via L1-norm regularized EM algorithm
CN115553794B (en) Three-dimensional Compton scattering imaging method and system based on parallel hole collimator
JP7681419B2 (en) Image processing device, image processing method, and tomographic image acquisition system
JP4864909B2 (en) Image processing device
Ahlers et al. High-energy X-ray phase-contrast CT of an adult human chest phantom
Shah et al. Photon-counting CT in cancer radiotherapy: technological advances and clinical benefits
Chen et al. X-ray fluorescence CT reconstruction based on residual encoder-decoder networks
Fan et al. Beam Hardening Correction for Image-Domain Material Decomposition in Photon-Counting CT
Yang et al. DDHANet: Dual-Domain Hybrid Attention-Guided Network For CT Scatter Correction
Us Reduction of Limited Angle Artifacts in Medical Tomography via Image Reconstruction
Haase et al. Estimation of statistical weights for model-based iterative CT reconstruction