Maldjian et al., 2016 - Google Patents
Multi-atlas library for eliminating normalization failures in non-human primatesMaldjian et al., 2016
View PDF- Document ID
- 9656687492434048513
- Author
- Maldjian J
- Shively C
- Nader M
- Friedman D
- Whitlow C
- Publication year
- Publication venue
- Neuroinformatics
External Links
Snippet
Current tools for automated skull stripping, normalization, and segmentation of non-human primate (NHP) brain MRI studies typically demonstrate high failure rates. Many of these failures are due to a poor initial estimate for the affine component of the transformation. The …
- 238000010606 normalization 0 title abstract description 51
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
- G06T2207/10088—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
- G06T2207/10—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
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
-
- 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
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Yassa et al. | A quantitative evaluation of cross-participant registration techniques for MRI studies of the medial temporal lobe | |
| Aubert-Broche et al. | A new method for structural volume analysis of longitudinal brain MRI data and its application in studying the growth trajectories of anatomical brain structures in childhood | |
| US7822291B2 (en) | Non-rigid multi-modal registration using statistical learning methods | |
| Romero et al. | CERES: a new cerebellum lobule segmentation method | |
| Fonov et al. | Unbiased average age-appropriate atlases for pediatric studies | |
| Sabuncu et al. | Image-driven population analysis through mixture modeling | |
| EP2690596B1 (en) | Method, apparatus and system for automated spine labeling | |
| Tohka et al. | Fast and robust parameter estimation for statistical partial volume models in brain MRI | |
| Xiao et al. | Multi-contrast unbiased MRI atlas of a Parkinson’s disease population | |
| Yan et al. | Machine learning in medical imaging | |
| Lu et al. | Fully automatic liver segmentation combining multi-dimensional graph cut with shape information in 3D CT images | |
| Mulder et al. | Size and shape matter: the impact of voxel geometry on the identification of small nuclei | |
| Koleilat et al. | Medclip-samv2: Towards universal text-driven medical image segmentation | |
| Cigdem et al. | Effects of different covariates and contrasts on classification of Parkinson's disease using structural MRI | |
| Alam et al. | Challenges and solutions in multimodal medical image subregion detection and registration | |
| Krokos et al. | A review of PET attenuation correction methods for PET-MR | |
| Murgasova et al. | Segmentation of brain MRI in young children | |
| Hopkins et al. | Regional and hemispheric variation in cortical thickness in chimpanzees (Pan troglodytes) | |
| Maldjian et al. | Multi-atlas library for eliminating normalization failures in non-human primates | |
| Osechinskiy et al. | Slice‐to‐volume nonrigid registration of histological sections to MR images of the human brain | |
| JP2024510080A (en) | Systems, devices and methods for harmonization of imaging datasets containing biomarkers | |
| Stæger et al. | A three-dimensional, population-based average of the C57BL/6 mouse brain from DAPI-stained coronal slices | |
| Maldjian et al. | Vervet MRI atlas and label map for fully automated morphometric analyses | |
| Panda et al. | Evaluation of multiatlas label fusion for in vivo magnetic resonance imaging orbital segmentation | |
| Lin et al. | A template‐based automatic skull‐stripping approach for mouse brain MR microscopy |