A similarity study between the query mass and retrieved masses using decision tree content-based image retrieval (DTCBIR) CADx system for characterization of ultrasound breast mass images

2012 ◽  
Author(s):  
Hyun-Chong Cho ◽  
Lubomir Hadjiiski ◽  
Heang-Ping Chan ◽  
Berkman Sahiner ◽  
Mark Helvie ◽  
...  
Keyword(s):  
Decision Tree ◽  
Image Retrieval ◽  
Breast Mass ◽  
Content Based Image Retrieval

scholarly journals A similarity study of content-based image retrieval system for breast cancer using decision tree

2012 ◽  
Vol 40 (1) ◽  
pp. 012901 ◽  
Author(s):  
Hyun-chong Cho ◽  
Lubomir Hadjiiski ◽  
Berkman Sahiner ◽  
Heang-Ping Chan ◽  
Mark Helvie ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Tree ◽  
Image Retrieval ◽  
Retrieval System ◽  
Content Based Image Retrieval ◽  
Image Retrieval System

scholarly journals Similarity evaluation in a content-based image retrieval (CBIR) CADx system for characterization of breast masses on ultrasound images

2011 ◽  
Vol 38 (4) ◽  
pp. 1820-1831 ◽  
Author(s):  
Hyun-chong Cho ◽  
Lubomir Hadjiiski ◽  
Berkman Sahiner ◽  
Heang-Ping Chan ◽  
Mark Helvie ◽  
...  
Keyword(s):  
Image Retrieval ◽  
Content Based Image Retrieval ◽  
Ultrasound Images ◽  
Breast Masses

scholarly journals Automatic Characterization of the Visual Appearance of Industrial Materials through Colour and Texture Analysis: An Overview of Methods and Applications

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Elena González ◽  
Francesco Bianconi ◽  
Marcos X. Álvarez ◽  
Stefano A. Saetta
Keyword(s):  
Customer Satisfaction ◽  
Image Retrieval ◽  
Texture Analysis ◽  
Content Based Image Retrieval ◽  
Surface Inspection ◽  
Visual Appearance ◽  
Advantages And Disadvantages ◽  
Potential Benefits ◽  
Industrial Materials

We present an overview of methods and applications of automatic characterization of the appearance of materials through colour and texture analysis. We propose a taxonomy based on three classes of methods (spectral, spatial, and hybrid) and discuss their general advantages and disadvantages. For each class we present a set of methods that are computationally cheap and easy to implement and that was proved to be reliable in many applications. We put these methods in the context of typical industrial environments and provide examples of their application in the following tasks: surface grading, surface inspection, and content-based image retrieval. We emphasize the potential benefits that would come from a wide implementation of these methods, such as better product quality, new services, and higher customer satisfaction.

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