Nothing Special   »   [go: up one dir, main page]

De Bruijne et al., 2004 - Google Patents

Interactive segmentation of abdominal aortic aneurysms in CTA images

De Bruijne et al., 2004

View PDF
Document ID
14139207650278234060
Author
De Bruijne M
van Ginneken B
Viergever M
Niessen W
Publication year
Publication venue
Medical image analysis

External Links

Snippet

A model-based approach to interactive segmentation of abdominal aortic aneurysms from CTA data is presented. After manual delineation of the aneurysm sac in the first slice, the method automatically detects the contour in subsequent slices, using the result from the …
Continue reading at image.diku.dk (PDF) (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
    • 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
    • G06T2207/10072—Tomographic images
    • G06T2207/10088—Magnetic resonance imaging [MRI]
    • 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
    • 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
    • G06T2207/20092—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
    • 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
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K2209/05—Recognition of patterns in medical or anatomical images

Similar Documents

Publication Publication Date Title
De Bruijne et al. Interactive segmentation of abdominal aortic aneurysms in CTA images
Lynch et al. Automatic segmentation of the left ventricle cavity and myocardium in MRI data
Queirós et al. Fast automatic myocardial segmentation in 4D cine CMR datasets
Sluimer et al. Toward automated segmentation of the pathological lung in CT
Litjens et al. Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge
US7519209B2 (en) System and methods of organ segmentation and applications of same
US7382907B2 (en) Segmenting occluded anatomical structures in medical images
Peters et al. Automatic whole heart segmentation in static magnetic resonance image volumes
Chen et al. Segmenting the prostate and rectum in CT imagery using anatomical constraints
Wan et al. Automated coronary artery tree segmentation in X-ray angiography using improved Hessian based enhancement and statistical region merging
de Bruijne et al. Active-shape-model-based segmentation of abdominal aortic aneurysms in CTA images
WO2012040410A9 (en) Method and system for liver lesion detection
Wang et al. Segmentation of lumen and outer wall of abdominal aortic aneurysms from 3D black-blood MRI with a registration based geodesic active contour model
Colliot et al. Segmentation of focal cortical dysplasia lesions on MRI using level set evolution
Zhu et al. Automatic delineation of the myocardial wall from CT images via shape segmentation and variational region growing
Vukadinovic et al. Segmentation of the outer vessel wall of the common carotid artery in CTA
Chen et al. Lumen and media-adventitia border detection in IVUS images using texture enhanced deformable model
US7747051B2 (en) Distance transform based vessel detection for nodule segmentation and analysis
Li et al. Integrating FCM and level sets for liver tumor segmentation
Dahiya et al. Integrated 3D anatomical model for automatic myocardial segmentation in cardiac CT imagery
Tosun et al. Cortical reconstruction using implicit surface evolution: accuracy and precision analysis
De Bruijne et al. Model-based segmentation of abdominal aortic aneurysms in CTA images
Hernandez et al. Three-dimensional segmentation of brain aneurysms in CTA using non-parametric region-based information and implicit deformable models: Method and evaluation
Onal et al. Image based measurements for evaluation of pelvic organ prolapse
Liu et al. Unsupervised 3D Prostate Segmentation Based on Diffusion‐Weighted Imaging MRI Using Active Contour Models with a Shape Prior