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

Yao et al., 2022 - Google Patents

Quantitative assessment for characterization of breast lesion tissues using adaptively decomposed ultrasound RF images

Yao et al., 2022

Document ID
18189816161722941878
Author
Yao R
Zhang Y
Wu K
Li Z
He M
Fengyue B
Publication year
Publication venue
Biomedical Signal Processing and Control

External Links

Snippet

Quantitative ultrasound is of significant relevance to the clinical diagnosis of benign and malignant breast lesions. Owing to desmoplastic reactions in the tumor and malignant cells invading the surrounding tissues, the irregular boundary of the lesion is a significant …
Continue reading at www.sciencedirect.com (other versions)

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
    • 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
    • G06T2207/10—Image acquisition modality
    • 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
    • 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
    • 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
    • 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
    • G06T5/007—Dynamic range modification
    • G06T5/008—Local, e.g. shadow enhancement

Similar Documents

Publication Publication Date Title
Hsu et al. Breast tumor classification using different features of quantitative ultrasound parametric images
Huang et al. Computer‐aided diagnosis using morphological features for classifying breast lesions on ultrasound
Acharya et al. Non-invasive automated 3D thyroid lesion classification in ultrasound: A class of ThyroScan™ systems
Acharya et al. ThyroScreen system: high resolution ultrasound thyroid image characterization into benign and malignant classes using novel combination of texture and discrete wavelet transform
Akbari et al. 3D ultrasound image segmentation using wavelet support vector machines
Mencattini et al. Metrological characterization of a CADx system for the classification of breast masses in mammograms
Moon et al. Computer-aided diagnosis based on speckle patterns in ultrasound images
Chowdhury et al. Ultrasound classification of breast masses using a comprehensive Nakagami imaging and machine learning framework
Nagarajan et al. Feature extraction based on empirical mode decomposition for automatic mass classification of mammogram images
Kim et al. Computerized scheme for assessing ultrasonographic features of breast masses1
Osapoetra et al. Breast lesion characterization using quantitative ultrasound (QUS) and derivative texture methods
Al-Kadi et al. Heterogeneous tissue characterization using ultrasound: a comparison of fractal analysis backscatter models on liver tumors
Koundal et al. Advanced neutrosophic set-based ultrasound image analysis
Ganvir et al. Filtering method for pre-processing mammogram images for breast cancer detection
Maggio et al. Predictive deconvolution and hybrid feature selection for computer-aided detection of prostate cancer
Femil et al. An Efficient Hybrid Optimization for Skin Cancer Detection Using PNN Classifier.
Yao et al. Quantitative assessment for characterization of breast lesion tissues using adaptively decomposed ultrasound RF images
Kaur et al. Computer-aided diagnosis of renal lesions in CT images: a comprehensive survey and future prospects
Muhtadi Breast tumor classification using intratumoral quantitative ultrasound descriptors
Han et al. Quantitative ultrasound parameters from scattering and propagation may reduce the biopsy rate for breast tumor
Sahba et al. A coarse-to-fine approach to prostate boundary segmentation in ultrasound images
Diao et al. Highly sensitive computer aided diagnosis system for breast tumor based on color Doppler flow images
Armya et al. Medical images segmentation based on unsupervised algorithms: a review
Muhtadi et al. Texture quantified from ultrasound Nakagami parametric images is diagnostically relevant for breast tumor characterization
Alacam et al. Breast tissue characterization using FARMA modeling of ultrasonic RF echo