Medical image classification based on multi-scale non-negative sparse coding

•We propose a multi-scale non-negative sparse coding model to construct visual dictionary thus to overcome the defects of BoVW-based algorithms.•We utilize multi-scale decomposition method to decompose images into multiple scale layers and extract more representative image features.•We introduce fis...

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Bibliographic Details
Published in:Artificial intelligence in medicine Vol. 83; pp. 44 - 51
Main Authors: Zhang, Ruijie, Shen, Jian, Wei, Fushan, Li, Xiong, Sangaiah, Arun Kumar
Format: Journal Article
Language:English
Published: Netherlands Elsevier B.V 01.11.2017
Subjects:
Artificial Intelligence
Diagnostic Imaging - classification
Fisher discriminative analysis
Humans
Image Interpretation, Computer-Assisted - methods
Internal Medicine
Medical image classification
Multi-scale decomposition
Non-negative sparse coding
Other
Pattern Recognition, Automated
Predictive Value of Tests
ROC Curve
The semantic gap
The semantic gap
Multi-scale decomposition
Non-negative sparse coding
Fisher discriminative analysis
Medical image classification
ISSN:0933-3657, 1873-2860, 1873-2860
Online Access:Get full text
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