[go: up one dir, main page]

Tian et al., 2013 - Google Patents

A flexible 3D cerebrovascular extraction from TOF-MRA images

Tian et al., 2013

Document ID
7377630975378395609
Author
Tian Y
Duan F
Lu K
Zhou M
Wu Z
Wang Q
Sun L
Xie L
Publication year
Publication venue
Neurocomputing

External Links

Snippet

For accurately extracting 3D cerebral tree from time-of-flight magnetic resonance angiography (TOF-MRA) images, a novel active contour model is presented by combining the statistical information and the vessel shape information in a variational level set …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • 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
    • G06T2207/10088Magnetic resonance imaging [MRI]
    • 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
    • G06T2207/10104Positron emission tomography [PET]
    • 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
    • G06T2207/30101Blood vessel; Artery; Vein; Vascular
    • 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
    • G06T2207/30048Heart; Cardiac
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20112Image segmentation details
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10024Color image
    • 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
    • G06T2207/30172Centreline of tubular or elongated structure
    • 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
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20076Probabilistic image processing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20212Image combination
    • G06T2207/20224Image subtraction
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
    • G06T5/007Dynamic range modification
    • G06T5/008Local, e.g. shadow enhancement
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING

Similar Documents

Publication Publication Date Title
Shang et al. Vascular active contour for vessel tree segmentation
Li et al. Integrating spatial fuzzy clustering with level set methods for automated medical image segmentation
El-Baz et al. Precise segmentation of 3-D magnetic resonance angiography
Sun et al. Local morphology fitting active contour for automatic vascular segmentation
Lynch et al. Automatic segmentation of the left ventricle cavity and myocardium in MRI data
Läthén et al. Blood vessel segmentation using multi-scale quadrature filtering
Duan et al. The $ L_ {0} $ regularized Mumford–Shah model for bias correction and segmentation of medical images
Göçeri Fully automated liver segmentation using Sobolev gradient‐based level set evolution
Göçeri et al. A comparative performance evaluation of various approaches for liver segmentation from SPIR images
Alirr et al. Survey on liver tumour resection planning system: steps, techniques, and parameters
Chung et al. Deeply self-supervised contour embedded neural network applied to liver segmentation
Lee et al. Segmentation of interest region in medical volume images using geometric deformable model
Huynh et al. Fully automated MR liver volumetry using watershed segmentation coupled with active contouring
Nguyen et al. Superpixel and multi-atlas based fusion entropic model for the segmentation of X-ray images
Zhu et al. Automatic delineation of the myocardial wall from CT images via shape segmentation and variational region growing
Zhang et al. Blood vessel enhancement for DSA images based on adaptive multi-scale filtering
Wang et al. Statistical tracking of tree-like tubular structures with efficient branching detection in 3D medical image data
Tian et al. A flexible 3D cerebrovascular extraction from TOF-MRA images
Hong et al. 3D vasculature segmentation using localized hybrid level-set method
Hameeteman et al. Carotid wall volume quantification from magnetic resonance images using deformable model fitting and learning-based correction of systematic errors
Tong et al. Automatic lumen border detection in IVUS images using dictionary learning and kernel sparse representation
Zhao et al. Multi-branched cerebrovascular segmentation based on phase-field and likelihood model
Bukenya et al. A review of blood vessel segmentation techniques
Zhao et al. Extraction of vessel networks based on multiview projection and phase field model
Veeramalla et al. Segmentation of MRI images using a combination of active contour modeling and morphological processing