[go: up one dir, main page]

Sen, 1996 - Google Patents

Three-dimensional reconstruction of cerebral vasculature from limited digital subtraction angiographic projections

Sen, 1996

Document ID
8237669917636872737
Author
Sen A
Publication year

External Links

Snippet

An integrated approach is developed for 3D cone beam reconstruction of cerebral vasculature (both morphology and gray scale) from a limited number (4-6) of digital subtraction angiographic (DSA) projections, obtained using a standard biplane C-arm x-ray …
Continue reading at search.proquest.com (other versions)

Classifications

    • 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
    • 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
    • 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
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • 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
    • G06T2211/00—Image generation
    • G06T2211/40—Computed tomography
    • 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
    • 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
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2200/00—Indexing scheme for image data processing or generation, in general
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
    • G06T3/0031—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image for topological mapping of a higher dimensional structure on a lower dimensional surface
    • G06T3/0037—Reshaping or unfolding a 3D tree structure onto a 2D plane
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T15/00—3D [Three Dimensional] image rendering
    • 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
    • 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
    • A61B6/50—Clinical applications
    • A61B6/507—Clinical applications involving determination of haemodynamic parameters, e.g. perfusion CT
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING

Similar Documents

Publication Publication Date Title
Thibault et al. A three‐dimensional statistical approach to improved image quality for multislice helical CT
Zhao et al. X-ray CT metal artifact reduction using wavelets: an application for imaging total hip prostheses
CN100553561C (en) The method and apparatus of segmenting structure in the CT angiography
CN109389655B (en) Reconstruction of time-varying data
CN111540025B (en) Predicting images for image processing
Kim et al. A rigid motion correction method for helical computed tomography (CT)
JP6755321B2 (en) A medical imaging system with a fixed array of X-ray detectors and a fixed array of X-ray emitters for generating digital 3D images
CN110337673A (en) Deep learning based estimation of data used in tomographic reconstruction
Kim et al. Cardiac motion correction based on partial angle reconstructed images in x‐ray CT
KR101591381B1 (en) Method for reducing metal artifact in computed tomography
JP3987024B2 (en) Method and system for enhancing tomosynthesis images using lateral filtering
US20170340287A1 (en) Method And Apparatus For Motion Correction In CT Imaging
CN102047295A (en) Reconstruction of dynamical cardiac SPECT for measuring tracer uptake and redistribution
Schnurr et al. Simulation-based deep artifact correction with convolutional neural networks for limited angle artifacts
Van Stevendaal et al. A motion‐compensated scheme for helical cone‐beam reconstruction in cardiac CT angiography
Lin et al. C^ 2rv: Cross-regional and cross-view learning for sparse-view cbct reconstruction
Jang et al. Head motion correction based on filtered backprojection for x‐ray CT imaging
CN102376084A (en) Iterative image filtering with anisotropic noise model for a CT image
Kim et al. Cardiac image reconstruction via nonlinear motion correction based on partial angle reconstructed images
EP1716537B1 (en) Apparatus and method for the processing of sectional images
Linney et al. Organ motion detection in CT images using opposite rays in fan-beam projection systems
Sen Three-dimensional reconstruction of cerebral vasculature from limited digital subtraction angiographic projections
Shen et al. Image Quality Enhancement for Digital Breast Tomosynthesis: High-Density Object Artifact Reduction
Choi et al. Chest tomosynthesis deblurring using CNN with deconvolution layer for vertebrae segmentation
Iserhardt-Bauer et al. Standardized analysis of intracranial aneurysms using digital video sequences