Forkel et al., 2018 - Google Patents
Lesion mapping in acute stroke aphasia and its implications for recoveryForkel et al., 2018
View HTML- Document ID
- 5282351034642758427
- Author
- Forkel S
- Catani M
- Publication year
- Publication venue
- Neuropsychologia
External Links
Snippet
Patients with stroke offer a unique window into understanding human brain function. Mapping stroke lesions poses several challenges due to the complexity of the lesion anatomy and the mechanisms causing local and remote disruption on brain networks. In this …
- 230000003902 lesions 0 title abstract description 97
Classifications
-
- 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
- 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]
-
- 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
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
- G06T7/0014—Biomedical image inspection using an image reference approach
-
- 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
- G06T2207/10084—Hybrid tomography; Concurrent acquisition with multiple different tomographic modalities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20092—Interactive image processing based on input by user
- G06T2207/20104—Interactive definition of region of interest [ROI]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20212—Image combination
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
- G06T3/0031—Geometric 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
- G06T3/0037—Reshaping or unfolding a 3D tree structure onto a 2D plane
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
-
- 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
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Forkel et al. | Lesion mapping in acute stroke aphasia and its implications for recovery | |
| Eskildsen et al. | BEaST: brain extraction based on nonlocal segmentation technique | |
| Yeh et al. | Diffusion MRI connectometry automatically reveals affected fiber pathways in individuals with chronic stroke | |
| Zhuang et al. | White matter integrity in mild cognitive impairment: a tract-based spatial statistics study | |
| Yu et al. | Multiple white matter tract abnormalities underlie cognitive impairment in RRMS | |
| EP2126609B1 (en) | Tools for aiding in the diagnosis of neurodegenerative diseases | |
| Nestor et al. | A direct morphometric comparison of five labeling protocols for multi-atlas driven automatic segmentation of the hippocampus in Alzheimer's disease | |
| Kim et al. | Automatic hippocampal segmentation in temporal lobe epilepsy: impact of developmental abnormalities | |
| US7787671B2 (en) | Method, system and storage medium which includes instructions for analyzing anatomical structures | |
| Reuter et al. | Impact of MRI head placement on glioma response assessment | |
| Christiansen et al. | The status of the precommissural and postcommissural fornix in normal ageing and mild cognitive impairment: An MRI tractography study | |
| Melzer et al. | Test-retest reliability and sample size estimates after MRI scanner relocation | |
| Froeling et al. | DTI analysis methods: region of interest analysis | |
| Peng et al. | Development of a human brain diffusion tensor template | |
| US20150356733A1 (en) | Medical image processing | |
| Horbruegger et al. | Anatomically constrained tractography facilitates biologically plausible fiber reconstruction of the optic radiation in multiple sclerosis | |
| Sun et al. | Automated template-based PET region of interest analyses in the aging brain | |
| Bigler | Structural neuroimaging in neuropsychology: History and contemporary applications. | |
| Steketee et al. | Concurrent white and gray matter degeneration of disease-specific networks in early-stage Alzheimer's disease and behavioral variant frontotemporal dementia | |
| Xiao et al. | Patch-based label fusion segmentation of brainstem structures with dual-contrast MRI for Parkinson’s disease | |
| Sanchez-Catasus et al. | Brain tissue volumes and perfusion change with the number of optic neuritis attacks in relapsing neuromyelitis optica: a voxel-based correlation study | |
| Oh et al. | Segmentation of white matter hyperintensities on 18F-FDG PET/CT images with a generative adversarial network | |
| Ravano et al. | Validating atlas-based lesion disconnectomics in multiple sclerosis: A retrospective multi-centric study | |
| Kancheva et al. | Investigating secondary white matter degeneration following ischemic stroke by modelling affected fiber tracts | |
| Huang et al. | Automatic oculomotor nerve identification based on data‐driven fiber clustering |