Love et al., 2016 - Google Patents
The average baboon brain: MRI templates and tissue probability maps from 89 individualsLove et al., 2016
View PDF- Document ID
- 12589930051733855444
- Author
- Love S
- Marie D
- Roth M
- Lacoste R
- Nazarian B
- Bertello A
- Coulon O
- Anton J
- Meguerditchian A
- Publication year
- Publication venue
- NeuroImage
External Links
Snippet
The baboon (Papio) brain is a remarkable model for investigating the brain. The current work aimed at creating a population-average baboon (Papio anubis) brain template and its left/right hemisphere symmetric version from a large sample of T1-weighted magnetic …
- 210000004556 Brain 0 title abstract description 92
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R33/00—Arrangements or instruments for measuring magnetic variables
- G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
- G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
- G01R33/48—NMR imaging systems
- G01R33/54—Signal processing systems, e.g. using pulse sequences, Generation or control of pulse sequences ; Operator Console
- G01R33/56—Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution
-
- 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
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R33/00—Arrangements or instruments for measuring magnetic variables
- G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
- G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
- G01R33/48—NMR imaging systems
- G01R33/4806—Functional imaging of brain activation
-
- 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
- G06T2207/10104—Positron emission tomography [PET]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
- A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radiowaves
- A61B5/055—Detecting, 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
-
- 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
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
- A61B5/0033—Features or image-related aspects of imaging apparatus classified in A61B5/00, e.g. for MRI, optical tomography or impedance tomography apparatus; arrangements of imaging apparatus in a room
- A61B5/004—Features or image-related aspects of imaging apparatus classified in A61B5/00, e.g. for MRI, optical tomography or impedance tomography apparatus; arrangements of imaging apparatus in a room adapted for image acquisition of a particular organ or body part
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Love et al. | The average baboon brain: MRI templates and tissue probability maps from 89 individuals | |
Seidlitz et al. | A population MRI brain template and analysis tools for the macaque | |
Li et al. | Mapping putative hubs in human, chimpanzee and rhesus macaque connectomes via diffusion tractography | |
Sui et al. | Discriminating schizophrenia and bipolar disorder by fusing fMRI and DTI in a multimodal CCA+ joint ICA model | |
Jin et al. | Automatic clustering of white matter fibers in brain diffusion MRI with an application to genetics | |
Fan et al. | Discriminant analysis of functional connectivity patterns on Grassmann manifold | |
Schwarz et al. | Negative edges and soft thresholding in complex network analysis of resting state functional connectivity data | |
Nie et al. | A rat brain MRI template with digital stereotaxic atlas of fine anatomical delineations in paxinos space and its automated application in voxel‐wise analysis | |
US10881321B2 (en) | Automatic tract extraction via atlas based adaptive connectivity-based clustering | |
Vázquez et al. | FFClust: fast fiber clustering for large tractography datasets for a detailed study of brain connectivity | |
Mulder et al. | Size and shape matter: the impact of voxel geometry on the identification of small nuclei | |
Feusner et al. | White matter microstructure in body dysmorphic disorder and its clinicalcorrelates | |
Liu et al. | Successful reorganization of category-selective visual cortex following occipito-temporal lobectomy in childhood | |
Tunç et al. | Automated tract extraction via atlas based adaptive clustering | |
Peng et al. | Development of a human brain diffusion tensor template | |
Dougherty et al. | Occipital‐Callosal Pathways in Children: Validation and Atlas Development | |
Gilaie-Dotan et al. | Perceptual shape sensitivity to upright and inverted faces is reflected in neuronal adaptation | |
Fantini et al. | Automatic MR image quality evaluation using a Deep CNN: A reference-free method to rate motion artifacts in neuroimaging | |
Buchanan et al. | Comparison of structural MRI brain measures between 1.5 and 3 T: Data from the Lothian Birth Cohort 1936 | |
Cohen-Adad et al. | In vivo DTI of the healthy and injured cat spinal cord at high spatial and angular resolution | |
Garcia-Garcia et al. | Detecting stable individual differences in the functional organization of the human basal ganglia | |
Zhong et al. | Flexible prediction of CT images from MRI data through improved neighborhood anchored regression for PET attenuation correction | |
Nitzken | Shape analysis of the human brain. | |
Ganzetti et al. | fMRI data processing in MRTOOL: to what extent does anatomical registration affect the reliability of functional results? | |
Blostein | Variation in subcortical anatomy: relating interspecies differences, heritability, and brain-behavior relationships |