Liu et al., 2015 - Google Patents

Thalamic nuclei segmentation in clinical 3T T1-weighted Images using high-resolution 7T shape models

Liu et al., 2015

View PDF
Document ID
1961002489284797603
Author
Liu Y
D'Haese P
Newton A
Dawant B
Publication year
Publication venue
Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling

External Links

Snippet

Accurate and reliable identification of thalamic nuclei is important for surgical interventions and neuroanatomical studies. This is a challenging task due to their small sizes and low intra-thalamic contrast in standard T1-weighted or T2-weighted images. Previously …
Continue reading at www.academia.edu (PDF) (other versions)

Classifications

    • 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
    • G01R33/563Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution of moving material, e.g. flow contrast angiography
    • G01R33/56341Diffusion imaging
    • 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
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10072Tomographic images
    • G06T2207/10084Hybrid tomography; Concurrent acquisition with multiple different tomographic modalities
    • 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
    • G01R33/28Details of apparatus provided for in groups G01R33/44 - G01R33/64
    • 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
    • G06T7/0014Biomedical image inspection using an image reference approach
    • 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
    • G06T3/0081Geometric 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 by elastic snapping
    • 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

Similar Documents

Publication Publication Date Title
Greve et al. Accurate and robust brain image alignment using boundary-based registration
Ceritoglu et al. Multi-contrast large deformation diffeomorphic metric mapping for diffusion tensor imaging
Zhang et al. Deformable registration of diffusion tensor MR images with explicit orientation optimization
Rohlfing et al. The SRI24 multichannel atlas of normal adult human brain structure
Aganj et al. A Hough transform global probabilistic approach to multiple-subject diffusion MRI tractography
Irfanoglu et al. DR-TAMAS: diffeomorphic registration for tensor accurate alignment of anatomical structures
Zhang et al. Mapping postnatal mouse brain development with diffusion tensor microimaging
Sergejeva et al. Anatomical landmarks for registration of experimental image data to volumetric rodent brain atlasing templates
Zhan et al. Spatial–temporal atlas of human fetal brain development during the early second trimester
Suarez et al. Automated delineation of white matter fiber tracts with a multiple region-of-interest approach
Liu et al. Generation of human thalamus atlases from 7 T data and application to intrathalamic nuclei segmentation in clinical 3 T T1-weighted images
US10753998B2 (en) Resolution enhancement of diffusion imaging biomarkers in magnetic resonance imaging
Barrick et al. Singularities in diffusion tensor fields and their relevance in white matter fiber tractography
Engstrom et al. Segmentation of the quadratus lumborum muscle using statistical shape modeling
WO2010005969A2 (en) Advanced cost functions for image registration for automated image analysis: multi-channel, hypertemplate and atlas with built-in variability
Little et al. Automated cerebral cortex segmentation based solely on diffusion tensor imaging for investigating cortical anisotropy
Liu et al. Thalamic nuclei segmentation in clinical 3T T1-weighted Images using high-resolution 7T shape models
Ehricke et al. Visualizing MR diffusion tensor fields by dynamic fiber tracking and uncertainty mapping
Bloy et al. White matter atlas generation using HARDI based automated parcellation
Hong et al. Spatial normalization of the fiber orientation distribution based on high angular resolution diffusion imaging data
Yap et al. PopTract: population-based tractography
Clayden et al. Reproducibility of tract segmentation between sessions using an unsupervised modelling-based approach
Studholme Dense feature deformation morphometry: Incorporating DTI data into conventional MRI morphometry
Eckstein et al. Active fibers: Matching deformable tract templates to diffusion tensor images
CN106030655B (en) Articulated structure registration in the magnetic resonance image of brain