patents.google.com

Luts et al., 2009 - Google Patents

  • ️Thu Jan 01 2009
Nosologic imaging of the brain: segmentation and classification using MRI and MRSI

Luts et al., 2009

View PDF
Document ID
6549513675018103632
Author
Laudadio T
Idema A
Simonetti A
Heerschap A
Vandermeulen D
Suykens J
Van Huffel S
Publication year
2009
Publication venue
NMR in Biomedicine: An International Journal Devoted to the Development and Application of Magnetic Resonance In vivo

External Links

Snippet

A new technique is presented to create nosologic images of the brain based on magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging (MRSI). A nosologic image summarizes the presence of different tissues and lesions in a single image …

Continue reading at www.academia.edu (PDF) (other versions)
  • 230000011218 segmentation 0 title abstract description 58

Classifications

    • 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
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20092Interactive image processing based on input by user
    • G06T2207/20104Interactive definition of region of interest [ROI]
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/345Medical expert systems, neural networks or other automated diagnosis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K2209/00Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K2209/05Recognition of patterns in medical or anatomical images
    • 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]

Similar Documents

Publication Publication Date Title
Luts et al. 2009 Nosologic imaging of the brain: segmentation and classification using MRI and MRSI
Cárdenes et al. 2009 A multidimensional segmentation evaluation for medical image data
US20100260396A1 (en) 2010-10-14 integrated segmentation and classification approach applied to medical applications analysis
Cai et al. 2020 Fully automated segmentation of head CT neuroanatomy using deep learning
Goncalves et al. 2014 Self-supervised MRI tissue segmentation by discriminative clustering
Zacharaki et al. 2011 Abnormality segmentation in brain images via distributed estimation
Bahadure et al. 2017 Feature extraction and selection with optimization technique for brain tumor detection from MR images
Radhakrishnan et al. 2020 Canny edge detection model in mri image segmentation using optimized parameter tuning method
van de Sande et al. 2023 A review of machine learning applications for the proton MR spectroscopy workflow
Menze et al. 2008 Mimicking the human expert: pattern recognition for an automated assessment of data quality in MR spectroscopic images
Wegmayr et al. 2019 Generative aging of brain MR-images and prediction of Alzheimer progression
Abdulkareem et al. 2022 Predicting post-contrast information from contrast agent free cardiac MRI using machine learning: Challenges and methods
US12033755B2 (en) 2024-07-09 Method and arrangement for identifying similar pre-stored medical datasets
Sanchez et al. 2023 FetMRQC: an open-source machine learning framework for multi-centric fetal brain MRI quality control
Belkacem-Boussaid et al. 2010 Computer-aided classification of centroblast cells in follicular lymphoma
Tran et al. 2013 High-dimensional MRI data analysis using a large-scale manifold learning approach
Anand et al. 2022 Detection of tumor affected part from histopathological bone images using morphological classification and recurrent convoluted neural networks
Saneipour et al. 2019 Improvement of MRI brain image segmentation using Fuzzy unsupervised learning
Saad et al. 2021 A review on image segmentation techniques for MRI brain stroke lesion
Noorizadeh et al. 2020 Multi-atlas based neonatal brain extraction using atlas library clustering and local label fusion
Pota et al. 2019 Multivariate fuzzy analysis of brain tissue volumes and relaxation rates for supporting the diagnosis of relapsing-remitting multiple sclerosis
Commowick et al. 2015 Diffusion MRI abnormalities detection with orientation distribution functions: A multiple sclerosis longitudinal study
Ouarda 2016 MR Brain Real Images Segmentation Based Modalities Fusion and Estimation Et Maximization Approach
Anderson et al. 2007 Automated classification of atherosclerotic plaque from magnetic resonance images using predictive models
Luts et al. 2011 Nosologic Imaging of Brain Tumors Using MRI and MRSI