[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Bhooshan et al., 2014 - Google Patents

Potential of computer‐aided diagnosis of high spectral and spatial resolution (HiSS) MRI in the classification of breast lesions

Bhooshan et al., 2014

View PDF @Full View
Document ID
2667596316822813225
Author
Bhooshan N
Giger M
Medved M
Li H
Wood A
Yuan Y
Lan L
Marquez A
Karczmar G
Newstead G
Publication year
Publication venue
Journal of Magnetic Resonance Imaging

External Links

Snippet

Purpose To compare the performance of computer‐aided diagnosis (CADx) analysis of precontrast high spectral and spatial resolution (HiSS) MRI to that of clinical dynamic contrast‐enhanced MRI (DCE‐MRI) in the diagnostic classification of breast lesions …
Continue reading at onlinelibrary.wiley.com (PDF) (other versions)

Classifications

    • 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]
    • G01R33/48NMR imaging systems
    • G01R33/54Signal processing systems, e.g. using pulse sequences, Generation or control of pulse sequences ; Operator Console
    • G01R33/56Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution
    • G01R33/563Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution of moving material, e.g. flow contrast angiography
    • G01R33/56341Diffusion imaging
    • 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]
    • G01R33/48NMR imaging systems
    • G01R33/54Signal processing systems, e.g. using pulse sequences, Generation or control of pulse sequences ; Operator Console
    • G01R33/56Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution
    • G01R33/5608Data processing and visualization specially adapted for MR, e.g. for feature analysis and pattern recognition on the basis of measured MR data, segmentation of measured MR data, edge contour detection on the basis of measured MR data, for enhancing measured MR data in terms of signal-to-noise ratio by means of noise filtering or apodization, for enhancing measured MR data in terms of resolution by means for deblurring, windowing, zero filling, or generation of gray-scaled images, colour-coded images or images displaying vectors instead of pixels
    • 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
    • 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
    • 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
    • G06T2207/10Image acquisition modality
    • G06T2207/10072Tomographic images
    • G06T2207/10084Hybrid tomography; Concurrent acquisition with multiple different tomographic modalities
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions

Similar Documents

Publication Publication Date Title
Cattell et al. Robustness of radiomic features in magnetic resonance imaging: review and a phantom study
Zhang et al. Radiomics based on multimodal MRI for the differential diagnosis of benign and malignant breast lesions
Parekh et al. Integrated radiomic framework for breast cancer and tumor biology using advanced machine learning and multiparametric MRI
Chitalia et al. Role of texture analysis in breast MRI as a cancer biomarker: A review
Liu et al. Radiomics analysis of apparent diffusion coefficient in cervical cancer: a preliminary study on histological grade evaluation
Bhooshan et al. Potential of computer‐aided diagnosis of high spectral and spatial resolution (HiSS) MRI in the classification of breast lesions
Cui et al. Predicting the ISUP grade of clear cell renal cell carcinoma with multiparametric MR and multiphase CT radiomics
Zhang et al. Automated deep learning method for whole‐breast segmentation in diffusion‐weighted breast MRI
Mayerhoefer et al. Texture‐based classification of focal liver lesions on MRI at 3.0 Tesla: A feasibility study in cysts and hemangiomas
Gibbs et al. Textural analysis of contrast‐enhanced MR images of the breast
Nagarajan et al. Classification of small lesions in breast MRI: evaluating the role of dynamically extracted texture features through feature selection
Vidić et al. Support vector machine for breast cancer classification using diffusion‐weighted MRI histogram features: Preliminary study
Partridge et al. Differential diagnosis of mammographically and clinically occult breast lesions on diffusion‐weighted MRI
Chen et al. Volumetric texture analysis of breast lesions on contrast‐enhanced magnetic resonance images
Suo et al. Characterization of breast masses as benign or malignant at 3.0 T MRI with whole‐lesion histogram analysis of the apparent diffusion coefficient
Saha et al. Breast cancer MRI radiomics: An overview of algorithmic features and impact of inter‐reader variability in annotating tumors
Lin et al. Template‐based automatic breast segmentation on MRI by excluding the chest region
Wan et al. A radio-genomics approach for identifying high risk estrogen receptor-positive breast cancers on DCE-MRI: preliminary results in predicting onco type DX risk scores
Park et al. Fast T2‐weighted imaging with deep learning‐based reconstruction: evaluation of image quality and diagnostic performance in patients undergoing radical prostatectomy
Agliozzo et al. Computer‐aided diagnosis for dynamic contrast‐enhanced breast MRI of mass‐like lesions using a multiparametric model combining a selection of morphological, kinetic, and spatiotemporal features
Ginsburg et al. Novel PCA‐VIP scheme for ranking MRI protocols and identifying computer‐extracted MRI measurements associated with central gland and peripheral zone prostate tumors
Aliotta et al. Extracting diffusion tensor fractional anisotropy and mean diffusivity from 3‐direction DWI scans using deep learning
Ohashi et al. Diagnostic performance of maximum slope: A kinetic parameter obtained from ultrafast dynamic contrast-enhanced magnetic resonance imaging of the breast using k-space weighted image contrast (KWIC)
Delbany et al. One‐millimeter isotropic breast diffusion‐weighted imaging: Evaluation of a superresolution strategy in terms of signal‐to‐noise ratio, sharpness and apparent diffusion coefficient
Liney et al. Breast lesion analysis of shape technique: semiautomated vs. manual morphological description