He et al., 2001 - Google Patents
Medial axis reformation: a new visualization method for CT angiographyHe et al., 2001
- Document ID
- 5325529317420761914
- Author
- He S
- Dai R
- Lu B
- Cao C
- Bai H
- Jing B
- Publication year
- Publication venue
- Academic Radiology
External Links
Snippet
RATIONALE AND OBJECTIVES: The authors performed this study to evaluate a new method (medial axis reformation [MAR]) for visualizing three-dimensional vascular data at electron-beam computed tomographic (CT) angiography. MATERIALS AND METHODS …
- 238000010968 computed tomography angiography 0 title abstract description 25
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
-
- 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
- G06T2207/20112—Image segmentation details
-
- 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
- G06T2207/20—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
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
-
- 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
- G06T2200/24—Indexing scheme for image data processing or generation, in general involving graphical user interfaces [GUIs]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/08—Volume rendering
-
- 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
- G06T19/00—Manipulating 3D models or images for computer graphics
-
- 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
- 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
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Sato et al. | Local maximum intensity projection (LMIP: A new rendering method for vascular visualization | |
| Soyer et al. | Three-dimensional helical CT of intrahepatic venous structures: comparison of three rendering techniques | |
| US20060074285A1 (en) | Apparatus and method for fusion and in-operating-room presentation of volumetric data and 3-D angiographic data | |
| Sieren et al. | Automated segmentation and quantification of the healthy and diseased aorta in CT angiographies using a dedicated deep learning approach | |
| Liao et al. | 3-D reconstruction of the coronary artery tree from multiple views of a rotational X-ray angiography | |
| Hernández-Hoyos et al. | Computer-assisted analysis of three-dimensional MR angiograms | |
| Verhoek et al. | Carotid bifurcation CT angiography: assessment of interactive volume rendering | |
| JP2002282235A (en) | Method for automatic segmentation of medical images | |
| He et al. | Medial axis reformation: a new visualization method for CT angiography | |
| JP4871292B2 (en) | System for visualizing anatomical tree structures | |
| JP2010528750A (en) | Inspection of tubular structures | |
| CN109498046A (en) | The myocardial infarction quantitative evaluating method merged based on nucleic image with CT coronary angiography | |
| CN112862833A (en) | Blood vessel segmentation method, electronic device and storage medium | |
| JP2834318B2 (en) | 3D image processing method | |
| JP4087517B2 (en) | Region extraction method | |
| Ropinski et al. | Multimodal vessel visualization of mouse aorta PET/CT scans | |
| Ho et al. | Comparative analysis of three-dimensional volume rendering and maximum intensity projection for preoperative planning in liver cancer | |
| Wood et al. | A method for measurement of cross sectional area, segment length, and branching angle of airway tree structures in situ | |
| Selle et al. | Analysis of the morphology and structure of vessel systems using skeletonization | |
| Kawata et al. | Measurement of blood vessel characteristics for disease detection based on cone-beam CT images | |
| Nyström et al. | Skeletonization of volumetric vascular images—distance information utilized for visualization | |
| Zhou et al. | CT angiography image postprocessing and data analysis | |
| Reimann et al. | Efficacy of computer aided analysis in detection of significant coronary artery stenosis in cardiac using dual source computed tomography | |
| Niki et al. | 3D diagnostic imaging of blood vessels using an X-ray rotational angiographic system | |
| Tam et al. | Volume rendering of abdominal aortic aneurysms |