[go: up one dir, main page]

Tang et al., 2006 - Google Patents

Surface extraction and thickness measurement of the articular cartilage from MR images using directional gradient vector flow snakes

Tang et al., 2006

View PDF
Document ID
2516702135832501896
Author
Tang J
Millington S
Acton S
Crandall J
Hurwitz S
Publication year
Publication venue
IEEE Transactions on Biomedical Engineering

External Links

Snippet

The accuracy of the surface extraction of magnetic resonance images of highly congruent joints with thin articular cartilage layers has a significant effect on the percentage errors and reproducibility of quantitative measurements (eg, thickness and volume) of the articular …
Continue reading at www.researchgate.net (PDF) (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
    • 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
    • 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
    • G06T2207/20Special algorithmic details
    • G06T2207/20112Image segmentation details
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00Arrangements or instruments for measuring magnetic variables
    • G01R33/20Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48NMR imaging systems
    • G01R33/54Signal processing systems, e.g. using pulse sequences, Generation or control of pulse sequences ; Operator Console
    • G01R33/56Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/05Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radiowaves
    • A61B5/055Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radiowaves involving electronic or nuclear magnetic resonance, e.g. magnetic resonance imaging
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/48Diagnostic techniques
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/08Detecting organic movements or changes, e.g. tumours, cysts, swellings
    • 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
    • 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
    • G06T3/0068Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image for image registration, e.g. elastic snapping

Similar Documents

Publication Publication Date Title
Tang et al. Surface extraction and thickness measurement of the articular cartilage from MR images using directional gradient vector flow snakes
US6799066B2 (en) Technique for manipulating medical images
Pedoia et al. Fully automatic analysis of the knee articular cartilage T1ρ relaxation time using voxel‐based relaxometry
Fripp et al. Automatic segmentation of the bone and extraction of the bone–cartilage interface from magnetic resonance images of the knee
Kauffmann et al. Computer-aided method for quantification of cartilage thickness and volume changes using MRI: validation study using a synthetic model
Fripp et al. Automatic segmentation and quantitative analysis of the articular cartilages from magnetic resonance images of the knee
Tamez-Pena et al. Unsupervised segmentation and quantification of anatomical knee features: data from the Osteoarthritis Initiative
Carballido-Gamio et al. Inter-subject comparison of MRI knee cartilage thickness
Jurek et al. CNN-based superresolution reconstruction of 3D MR images using thick-slice scans
EP2149121B1 (en) Image registration method
Zook et al. Statistical analysis of fractal-based brain tumor detection algorithms
Carballido-Gamio et al. Combined image processing techniques for characterization of MRI cartilage of the knee
Dupont et al. Fully-integrated framework for the segmentation and registration of the spinal cord white and gray matter
Cashman et al. Automated techniques for visualization and mapping of articular cartilage in MR images of the osteoarthritic knee: a base technique for the assessment of microdamage and submicro damage
Kumar et al. Knee articular cartilage segmentation from MR images: A review
Yang et al. Automatic bone segmentation and bone-cartilage interface extraction for the shoulder joint from magnetic resonance images
WO2009052562A1 (en) Automatic segmentation of articular cartilage in mr images
Myller et al. Method for segmentation of knee articular cartilages based on contrast-enhanced CT images
Jaremko et al. Reliability of an efficient MRI-based method for estimation of knee cartilage volume using surface registration
Millington et al. Quantitative and topographical evaluation of ankle articular cartilage using high resolution MRI
Włodarczyk et al. Fast automated segmentation of wrist bones in magnetic resonance images
Kubassova et al. Quantitative analysis of dynamic contrast-enhanced MRI datasets of the metacarpophalangeal joints
Sun et al. Discussions of knee joint segmentation
Fripp et al. Segmentation of the bones in MRIs of the knee using phase, magnitude, and shape information
Cheong et al. Development of semi-automatic segmentation methods for measuring tibial cartilage volume