+

Sargent et al., 2017 - Google Patents

Semi-automatic 3D lung nodule segmentation in CT using dynamic programming

Sargent et al., 2017

Document ID
9740062026740769073
Author
Sargent D
Park S
Publication year
Publication venue
Medical Imaging 2017: Image Processing

External Links

Snippet

We present a method for semi-automatic segmentation of lung nodules in chest CT that can be extended to general lesion segmentation in multiple modalities. Most semi-automatic algorithms for lesion segmentation or similar tasks use region-growing or edge-based …
Continue reading at www.spiedigitallibrary.org (other versions)

Classifications

    • 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
    • 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
    • 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
    • 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
    • G06T11/002D [Two Dimensional] image generation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/60Analysis of geometric attributes
    • 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
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2200/00Indexing scheme for image data processing or generation, in general
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
    • G06T3/0031Geometric 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
    • G06T3/0037Reshaping or unfolding a 3D tree structure onto a 2D plane
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications

Similar Documents

Publication Publication Date Title
Wunderling et al. Comparison of thyroid segmentation techniques for 3D ultrasound
Echegaray et al. Core samples for radiomics features that are insensitive to tumor segmentation: method and pilot study using CT images of hepatocellular carcinoma
Suzani et al. Semi-automatic segmentation of vertebral bodies in volumetric MR images using a statistical shape+ pose model
Mastmeyer et al. Random forest classification of large volume structures for visuo-haptic rendering in CT images
US9082193B2 (en) Shape-based image segmentation
Poudel et al. Active contours extension and similarity indicators for improved 3D segmentation of thyroid ultrasound images
Kuo et al. Segmentation of breast masses on dedicated breast computed tomography and three-dimensional breast ultrasound images
Sargent et al. Semi-automatic 3D lung nodule segmentation in CT using dynamic programming
US7684602B2 (en) Method and system for local visualization for tubular structures
Amran et al. BV-GAN: 3D time-of-flight magnetic resonance angiography cerebrovascular vessel segmentation using adversarial CNNs
Şekeroğlu et al. A computer aided diagnosis system for lung cancer detection using support vector machine
Shahedi et al. A semiautomatic algorithm for three-dimensional segmentation of the prostate on CT images using shape and local texture characteristics
Ogiela et al. Automatic segmentation of the carotid artery bifurcation region with a region-growing approach
Martel et al. Breast segmentation in MRI using Poisson surface reconstruction initialized with random forest edge detection
Cheng et al. Automatic centerline detection of small three-dimensional vessel structures
Pöhlmann et al. Three-dimensional segmentation of breast masses from digital breast tomosynthesis images
Zheng et al. Coordinate-guided U-Net for automated breast segmentation on MRI images
Zhang et al. A hybrid segmentation method for partitioning the liver based on 4D DCE-MR images
Hu et al. Centerline-based vessel segmentation using graph cuts
Yuan et al. A method for automatic liver segmentation from multi-phase contrast-enhanced CT images
Abdalbari et al. Segmentation of the liver from abdominal MR images: a level-set approach
Fotin et al. Workflow improvements for digital breast tomosynthesis: computerized generation of enhanced synthetic images
Hoye et al. A method to assess the performance and the relevance of segmentation in radiomic characterization
Park et al. Tumor propagation model using generalized hidden Markov model
Usta et al. Comparison of myocardial scar geometries from 2D and 3D LGE-MRI
点击 这是indexloc提供的php浏览器服务,不要输入任何密码和下载