Skip to Main content Skip to Navigation
Book sections

Intelligent Information Description and Recognition in Biomedical Image Databases

Abstract : There is a significant increase in the use of biomedical images in clinical medicine, disease research, and education. While the literature lists several successful methods that were developed and implemented for content-based image retrieval and recognition, they have been unable to make significant inroads in biomedical image recognition domain. The use of computer-aided diagnosis has been increasing. It is based on descriptors extraction and classification approaches. This interest is due to the need for specialized methods, which are specific to each biomedical image type, and also due to the lack of advances in image recognition systems. In this chapter, the authors present intelligent information description techniques and the most used classification methods in an image retrieval and recognition system. A multicriteria classification method applied for sickle cells disease image databases is given. The recognition performance system is illustrated and discussed.
Document type :
Book sections
Complete list of metadata
Contributor : Frédéric Davesne Connect in order to contact the contributor
Submitted on : Wednesday, November 30, 2011 - 7:07:30 PM
Last modification on : Tuesday, June 30, 2020 - 11:56:08 AM




Khalifa Djemal, Hichem Maaref. Intelligent Information Description and Recognition in Biomedical Image Databases. Boris Igelnik. Computational Modeling and Simulation of Intellect: Current State and Future Perspectives, IGI Global, pp.52--80, 2011, ⟨10.4018/978-1-60960-551-3.ch003⟩. ⟨hal-00646858⟩



Record views