Population-Based Incremental Interactive Concept Learning for Image Retrieval by Stochastic String Segmentations S. Ghebreab, C. C. Jaffe, A. W. M. Smeulders In IEEE Transactions on Medical Imaging 2004. [bibtex] [pdf] [url]

We propose a method for concept-based medical image retrieval that is a superset of existing semantic-based image retrieval methods. We conceive of a concept as an incremental and interactive formalization of the user's conception of an object in an image. The premise is that such a concept is closely related to a user's specific preferences and subjectivity and, thus, allows to deal with the complexity and content-dependency of medical image content. We describe an object in terms of multiple continuous boundary features and represent an object concept by the stochastic characteristics of an object population. A population-based incrementally learning technique, in combination with relevance feedback, is then used for concept customization. The user determines the speed and direction of concept customization using a single parameter that defines the degree of exploration and exploitation of the search space. Images are retrieved from a database in a limited number of steps based upon the customized concept. To demonstrate our method we have performed concept-based image retrieval on a database of 292 digitized X-ray images of cervical vertebrae with a variety of abnormalities. The results show that our method produces precise and accurate results when doing a direct search. In an open-ended search our method efficiently and effectively explores the search space.

@Article{GhebreabTMI2004,
  author       = "Ghebreab, S. and Jaffe, C. C. and Smeulders, A. W. M.",
  title        = "Population-Based Incremental Interactive Concept Learning for Image Retrieval by Stochastic String Segmentations",
  journal      = "IEEE Transactions on Medical Imaging",
  number       = "6",
  volume       = "23",
  pages        = "676--689",
  year         = "2004",
  url          = "https://ivi.fnwi.uva.nl/isis/publications/2004/GhebreabTMI2004",
  pdf          = "https://ivi.fnwi.uva.nl/isis/publications/2004/GhebreabTMI2004/GhebreabTMI2004.pdf",
  has_image    = 1
}