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Local ternary co-occurrence patterns: A new feature descriptor for MRI and CT image retrieval

https://doi.org/10.1016/j.neucom.2013.03.018
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Outgoing claims: the papers this work cites, builds on, or argues with.

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The ImageCLEFmed Medical Image Retrieval Task Test Collection
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Evaluation of Objective Similarity Measures for Selecting Similar Images of Mammographic Lesions
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Linear Models of Cumulative Distribution Function for Content-based Medical Image Retrieval
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Evaluation of a Content-Based Retrieval System for Blood Cell Images with Automated Methods
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Classification of Benign and Malignant Breast Masses Based on Shape and Texture Features in Sonography Images
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Directional Binary Wavelet Patterns for Biomedical Image Indexing and Retrieval
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Directional local extrema patterns: a new descriptor for content based image retrieval
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A comparative study of texture measures with classification based on featured distributions
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Wavelet optimization for content-based image retrieval in medical databases
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A comprehensive review of current local features for computer vision
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Using relevance feedback with short-term memory for content-based spine X-ray image retrieval
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Pyramid binary pattern features for real-time pedestrian detection from infrared videos
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Neighborhood preserving regression for image retrieval
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Shift and gray scale invariant features for palmprint identification using complex directional wavelet and local binary pattern
inferredcites →https://doi.org/10.1016/j.neucom.2012.06.031openalex-snapshot
Moment-based local binary patterns: A novel descriptor for invariant pattern recognition applications
inferredcites →https://doi.org/10.1016/j.patcog.2009.08.017openalex-snapshot
Rotation invariant texture classification using LBP variance (LBPV) with global matching
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PLBP: An effective local binary patterns texture descriptor with pyramid representation
inferredcites →https://doi.org/10.1016/j.patcog.2012.04.003openalex-snapshot
Discriminative features for texture description
inferredcites →https://doi.org/10.1016/j.patcog.2012.04.007openalex-snapshot
A simple method for improving local binary patterns by considering non-uniform patterns
inferredcites →https://doi.org/10.1016/j.sigpro.2011.12.005openalex-snapshot
Local maximum edge binary patterns: A new descriptor for image retrieval and object tracking
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Retrieval of translated, rotated and scaled color textures
inferredcites →https://doi.org/10.1016/s0925-2312(01)00344-7openalex-snapshot
An image retrieval system by impression words and specific object names–IRIS
inferredcites →https://doi.org/10.1016/s0925-2312(02)00604-5openalex-snapshot
On relevance feedback and similarity measure for image retrieval with synergetic neural nets
inferredcites →https://doi.org/10.1109/cbms.2003.1212781openalex-snapshot
MultiWaveMed: a system for medical image retrieval through wavelets transformations
inferredcites →https://doi.org/10.1109/cbms.2003.1212785openalex-snapshot
Retrieval by content of medical images using texture for tissue identification
inferredcites →https://doi.org/10.1109/tip.2009.2035882openalex-snapshot
Local Derivative Pattern Versus Local Binary Pattern: Face Recognition With High-Order Local Pattern Descriptor
inferredcites →https://doi.org/10.1109/tip.2010.2042645openalex-snapshot
Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions
inferredcites →https://doi.org/10.1109/tip.2010.2044957openalex-snapshot
A Completed Modeling of Local Binary Pattern Operator for Texture Classification
inferredcites →https://doi.org/10.1109/tip.2012.2188809openalex-snapshot
Local Tetra Patterns: A New Feature Descriptor for Content-Based Image Retrieval
inferredcites →https://doi.org/10.1109/tmi.2009.2038575openalex-snapshot
Quantitative Analysis of Pulmonary Emphysema Using Local Binary Patterns
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A Boosting Framework for Visuality-Preserving Distance Metric Learning and Its Application to Medical Image Retrieval
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Comparing features sets for content-based image retrieval in a medical-case database
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Open Access Series of Imaging Studies (OASIS): Cross-sectional MRI Data in Young, Middle Aged, Nondemented, and Demented Older Adults

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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