Nothing Special   »   [go: up one dir, main page]

Ganeshan et al., 2009 - Google Patents

Texture analysis in non-contrast enhanced CT: impact of malignancy on texture in apparently disease-free areas of the liver

Ganeshan et al., 2009

View PDF
Document ID
4244856154171834994
Author
Ganeshan B
Miles K
Young R
Chatwin C
Publication year
Publication venue
European journal of radiology

External Links

Snippet

OBJECTIVES: To determine whether texture analysis of non-contrast enhanced computed tomography (CT) images in apparently disease-free areas of the liver is altered by the presence of extra-and intra-hepatic malignancy in colorectal cancer patients. MATERIALS …
Continue reading at www.researchgate.net (PDF) (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
    • G06T2207/10072—Tomographic images
    • G06T2207/10084—Hybrid tomography; Concurrent acquisition with multiple different tomographic modalities
    • 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
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10116—X-ray image
    • 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
    • G06T2207/20048—Transform domain processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
    • G06T3/0031—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image for topological mapping of a higher dimensional structure on a lower dimensional surface
    • G06T3/0037—Reshaping or unfolding a 3D tree structure onto a 2D plane
    • 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
    • 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
    • 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

Similar Documents

Publication Publication Date Title
Ganeshan et al. Texture analysis in non-contrast enhanced CT: impact of malignancy on texture in apparently disease-free areas of the liver
Chitalia et al. Role of texture analysis in breast MRI as a cancer biomarker: A review
Cattell et al. Robustness of radiomic features in magnetic resonance imaging: review and a phantom study
Davnall et al. Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice?
US20200372281A1 (en) Method, apparatus and computer program for analysing medical image data
Nayak et al. Computer-aided diagnosis of cirrhosis and hepatocellular carcinoma using multi-phase abdomen CT
Ganeshan et al. Quantifying tumour heterogeneity with CT
Zheng et al. Parenchymal texture analysis in digital mammography: A fully automated pipeline for breast cancer risk assessment
Ganeshan et al. Hepatic enhancement in colorectal cancer: texture analysis correlates with hepatic hemodynamics and patient survival
Tan et al. Segmentation of lung lesions on CT scans using watershed, active contours, and Markov random field
Xu et al. Texture analysis on 18 F-FDG PET/CT images to differentiate malignant and benign bone and soft-tissue lesions
Song et al. Volumetric texture features from higher-order images for diagnosis of colon lesions via CT colonography
Arodź et al. Detection of clustered microcalcifications in small field digital mammography
US8144953B2 (en) Multi-scale analysis of signal enhancement in breast MRI
Ganeshan et al. In search of biologic correlates for liver texture on portal-phase CT
US8331641B2 (en) System and method for automatically classifying regions-of-interest
US8090172B2 (en) Robust segmentation of breast and muscle in MRI
US8160344B2 (en) Iterative segmentation of images for computer-aided detection
Caresio et al. Quantitative analysis of thyroid tumors vascularity: A comparison between 3‐D contrast‐enhanced ultrasound and 3‐D Power Doppler on benign and malignant thyroid nodules
Kaur et al. Computer-aided diagnosis of renal lesions in CT images: a comprehensive survey and future prospects
Hasan et al. A classification model of breast masses in DCE-MRI using kinetic curves features with quantum-Raina’s polynomial based fusion
Zielinski et al. Two-dimensional ARMA modeling for breast cancer detection and classification
Jaglan et al. Escalate the efficacy of breast tumor detection through magnetic resonance imaging: a framework
Delogu et al. Preprocessing methods for nodule detection in lung CT
Thangaraju et al. Detection of microcalcification clusters using hessian matrix and foveal segmentation method on multiscale analysis in digital mammograms