[go: up one dir, main page]

Yun et al., 2016 - Google Patents

Stenosis map for volume visualization of constricted tubular structures: Application to coronary artery stenosis

Yun et al., 2016

Document ID
16743163568105864967
Author
Yun J
Kim Y
Chun E
Shin Y
Lee J
Kim B
Publication year
Publication venue
Computer Methods and Programs in Biomedicine

External Links

Snippet

Although direct volume rendering (DVR) has become a commodity, effective rendering of interesting features is still a challenge. In one of active DVR application fields, the medicine, radiologists have used DVR for the diagnosis of lesions or diseases that should be …
Continue reading at www.sciencedirect.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
    • G06T2207/30101—Blood vessel; Artery; Vein; Vascular
    • 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
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10088—Magnetic resonance imaging [MRI]
    • 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
    • G06T7/0014—Biomedical image inspection using an image reference approach
    • 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
    • G06T2207/10081—Computed x-ray tomography [CT]
    • 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
    • G06T2207/20112—Image segmentation details
    • G06T2207/20156—Automatic seed setting
    • 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
    • G06T2207/20092—Interactive image processing based on input by user
    • G06T2207/20101—Interactive definition of point of interest, landmark or seed
    • 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
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30172—Centreline of tubular or elongated structure
    • 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
    • G06T2207/20212—Image combination
    • G06T2207/20224—Image subtraction
    • 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
    • G06T5/007—Dynamic range modification
    • G06T5/008—Local, e.g. shadow enhancement
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • 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
    • G06T2200/00—Indexing scheme for image data processing or generation, in general

Similar Documents

Publication Publication Date Title
Shikata et al. Automated segmentation of pulmonary vascular tree from 3D CT images
Zreik et al. Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis
JP6877868B2 (en) Image processing equipment, image processing method and image processing program
Kostis et al. Three-dimensional segmentation and growth-rate estimation of small pulmonary nodules in helical CT images
US7272250B2 (en) Vessel segmentation with nodule detection
US7397937B2 (en) Region growing in anatomical images
Zhou et al. Automatic multiscale enhancement and segmentation of pulmonary vessels in CT pulmonary angiography images for CAD applications
Oeltze et al. Interactive visual analysis of perfusion data
US9235887B2 (en) Classification of biological tissue by multi-mode data registration, segmentation and characterization
US7965810B2 (en) Device and method for identifying occlusions
Reeves et al. Computer-aided diagnosis for lung cancer
JP5081390B2 (en) Method and system for monitoring tumor burden
Azhari et al. Brain tumor detection and localization in magnetic resonance imaging
Sreeja et al. An improved feature based image fusion technique for enhancement of liver lesions
US7486812B2 (en) Shape estimates and temporal registration of lesions and nodules
Zhou et al. Automated coronary artery tree extraction in coronary CT angiography using a multiscale enhancement and dynamic balloon tracking (MSCAR-DBT) method
Wei et al. Computerized detection of noncalcified plaques in coronary CT angiography: evaluation of topological soft gradient prescreening method and luminal analysis
WO2014107402A1 (en) Classification of biological tissue by multi-mode data registration, segmentation and characterization
Sangsefidi et al. Balancing the data term of graph-cuts algorithm to improve segmentation of hepatic vascular structures
Slama et al. V-NET-VGG16: Hybrid deep learning architecture for optimal segmentation and classification of multi-differentiated liver tumors
Chen et al. Automatic 3D coronary artery segmentation based on local region active contour model
Jawaid et al. A hybrid energy model for region based curve evolution–Application to CTA coronary segmentation
US7747051B2 (en) Distance transform based vessel detection for nodule segmentation and analysis
He et al. 3-D B-spline wavelet-based local standard deviation (BWLSD): its application to edge detection and vascular segmentation in magnetic resonance angiography
Yun et al. Stenosis map for volume visualization of constricted tubular structures: Application to coronary artery stenosis