Huang et al., 2003 - Google Patents
Tumour grading from magnetic resonance spectroscopy: a comparison of feature extraction with variable selectionHuang et al., 2003
- Document ID
- 1113763777352520303
- Author
- Huang Y
- Lisboa P
- El‐Deredy W
- Publication year
- Publication venue
- Statistics in medicine
External Links
Snippet
Magnetic resonance spectroscopy (MRS) provides a non‐invasive measurement of the biochemistry of living tissue. However, signal variation due to tissue heterogeneity causes considerable mixing between different disease categories, making accurate class …
- 238000004611 spectroscopical analysis 0 title abstract description 15
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6261—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation partitioning the feature space
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
-
- 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]
- G01R33/46—NMR spectroscopy
- G01R33/4625—Processing of acquired signals, e.g. elimination of phase errors, baseline fitting, chemometric analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6279—Classification techniques relating to the number of classes
-
- 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]
- G01R33/46—NMR spectroscopy
- G01R33/465—NMR spectroscopy applied to biological material, e.g. in vitro testing
-
- 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
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00496—Recognising patterns in signals and combinations thereof
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
-
- 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
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K2209/05—Recognition of patterns in medical or anatomical images
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Huang et al. | Tumour grading from magnetic resonance spectroscopy: a comparison of feature extraction with variable selection | |
| Toivonen et al. | Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization | |
| Goutte et al. | Feature‐space clustering for fMRI meta‐analysis | |
| Devos et al. | Classification of brain tumours using short echo time 1H MR spectra | |
| US20040111220A1 (en) | Methods of decomposing complex data | |
| Luts et al. | Nosologic imaging of the brain: segmentation and classification using MRI and MRSI | |
| Yang et al. | Discrete wavelet transform-based whole-spectral and subspectral analysis for improved brain tumor clustering using single voxel MR spectroscopy | |
| Yang et al. | Manifold Learning in MR spectroscopy using nonlinear dimensionality reduction and unsupervised clustering | |
| Lee et al. | Factor analysis in personality research | |
| Constantin et al. | Identifying malignant transformations in recurrent low grade gliomas using high resolution magic angle spinning spectroscopy | |
| Acquarelli et al. | Convolutional neural networks to predict brain tumor grades and Alzheimer’s disease with MR spectroscopic imaging data | |
| Guo et al. | A spatial Bayesian latent factor model for image‐on‐image regression | |
| Lisboa et al. | Assessment of statistical and neural networks methods in NMR spectral classification and metabolite selection | |
| Andrearczyk et al. | Learning cross-protocol radiomics and deep feature standardization from CT images of texture phantoms | |
| Trigui et al. | A classification approach to prostate cancer localization in 3T multi-parametric MRI | |
| Xiang et al. | Multivariate analysis of Brillouin imaging data by supervised and unsupervised learning | |
| Migdadi et al. | Novelty detection for metabolic dynamics established on breast cancer tissue using 2D NMR TOCSY spectra | |
| Lee et al. | Robust methodology for the discrimination of brain tumours from in vivo magnetic resonance spectra | |
| US11402452B2 (en) | System and methods for dynamic covariance estimation of a multivariate signal | |
| Olivetti et al. | Brain decoding: biases in error estimation | |
| Ortega-Martorell et al. | Pattern recognition analysis of MR spectra | |
| Ghasemi et al. | Accurate grading of brain gliomas by soft independent modeling of class analogy based on non‐negative matrix factorization of proton magnetic resonance spectra | |
| Meyer et al. | Classification of fMRI time series in a low-dimensional subspace with a spatial prior | |
| Moinian et al. | Towards automated in vivo parcellation of the human cerebral cortex using supervised classification of magnetic resonance fingerprinting residuals | |
| Lee et al. | Tumor segmentation using temporal independent component analysis for DCE-MRI |