[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Dehmeshki et al., 2008 - Google Patents

Segmentation of pulmonary nodules in thoracic CT scans: a region growing approach

Dehmeshki et al., 2008

View PDF
Document ID
1126331401355514937
Author
Dehmeshki J
Amin H
Valdivieso M
Ye X
Publication year
Publication venue
IEEE transactions on medical imaging

External Links

Snippet

This paper presents an efficient algorithm for segmenting different types of pulmonary nodules including high and low contrast nodules, nodules with vasculature attachment, and nodules in the close vicinity of the lung wall or diaphragm. The algorithm performs an …
Continue reading at eprints.kingston.ac.uk (PDF) (other versions)

Classifications

    • 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
    • G06T2207/10Image 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
    • G06T2207/20Special algorithmic details
    • G06T2207/20112Image segmentation details
    • G06T2207/20156Automatic seed setting
    • 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
    • G06T2207/10Image acquisition modality
    • G06T2207/10072Tomographic images
    • G06T2207/10081Computed x-ray tomography [CT]
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20092Interactive image processing based on input by user
    • G06T2207/20101Interactive definition of point of interest, landmark or seed
    • 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
    • G06T2207/20Special algorithmic details
    • G06T2207/20112Image segmentation details
    • G06T2207/20116Active contour; Active surface; Snakes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10116X-ray image
    • 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
    • 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
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • 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
    • G06K2209/00Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K2209/05Recognition of patterns in medical or anatomical images
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2200/00Indexing scheme for image data processing or generation, in general

Similar Documents

Publication Publication Date Title
Dehmeshki et al. Segmentation of pulmonary nodules in thoracic CT scans: a region growing approach
Zhang et al. Atlas-driven lung lobe segmentation in volumetric X-ray CT images
Li et al. Computerized radiographic mass detection. I. Lesion site selection by morphological enhancement and contextual segmentation
Masutani et al. Computerized detection of pulmonary embolism in spiral CT angiography based on volumetric image analysis
Timp et al. A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography
Campadelli et al. A fully automated method for lung nodule detection from postero-anterior chest radiographs
Kubota et al. Segmentation of pulmonary nodules of various densities with morphological approaches and convexity models
Sluimer et al. Toward automated segmentation of the pathological lung in CT
Raba et al. Breast segmentation with pectoral muscle suppression on digital mammograms
EP2070045B1 (en) Advanced computer-aided diagnosis of lung nodules
Kumar et al. Automatic liver and lesion segmentation: a primary step in diagnosis of liver diseases
Ochs et al. Automated classification of lung bronchovascular anatomy in CT using AdaBoost
EP1883047A2 (en) Nodule boundary detection
US9230320B2 (en) Computer aided diagnostic system incorporating shape analysis for diagnosing malignant lung nodules
US20100111386A1 (en) Computer aided diagnostic system incorporating lung segmentation and registration
Priyadarsini et al. Survey on segmentation of liver from CT images
Casiraghi et al. Automatic abdominal organ segmentation from CT images
Soltaninejad et al. Lung nodule detection by KNN classifier and active contour modelling and 3D visualization
Lee et al. Efficient liver segmentation exploiting level-set speed images with 2.5 D shape propagation
Lim et al. Segmentation of the liver using the deformable contour method on CT images
Gupta et al. Methods for increased sensitivity and scope in automatic segmentation and detection of lung nodules in CT images
Novo et al. 3D lung nodule candidate detection in multiple scales
Van Ginneken Supervised probabilistic segmentation of pulmonary nodules in CT scans
Wu et al. Regulated morphology approach to fuzzy shape analysis with application to blood vessel extraction in thoracic CT scans
US8224051B2 (en) Method for detection of linear structures and microcalcifications in mammographic images