Abstract. This paper presents a framework to analyse visual patterns in a collection of medical images in a two stage procedure. First, a set of representative visual patterns from the image collection is obtained by constructing a visual-word dictionary under a bag-of-features approach. Second, an analysis of the relationships between visual patterns and semantic concepts in the image collection is performed. The most important visual patterns for each semantic concept are identified using correlation analysis. A matrix visualization of the structure and organization of the image collection is generated using a cluster analysis. The experimental evaluation was conducted on a histopathology image collection and results showed clear relationships between visual patterns and semantic concepts, that in addition, are of easy interpretation and understanding.
In another study, image-level retrieval of four special types of skin cancer REF was performed by constructing a visual word dictionary using a bag-of-features approach in order to represent a relationship between visual patterns and semantic concepts.
Visual Pattern Analysis in Histopathology Images Using Bag of Features
CIARP
Computer Science