Fr. 189.00

Artificial Intelligence in Recognition and Classification of Astrophysical and Medical Images

Anglais · Livre Relié

Expédition généralement dans un délai de 6 à 7 semaines

Description

En savoir plus

During the past decade digital imaging has significantly progressed in all imaging areas ranging from medicine, pharmacy, chemistry, biology to astrophysics, meteorology and geophysics. The avalanche of digitized images produced a need for special techniques of processing and knowledge extraction from many digital images with minimal or even without human interaction. This has resulted in a new area in the digital processing called pattern recognition that becomes increasingly necessary owing to a growing number of images to be processed. The first applications of pattern recognition techniques were for the analysis of medical X rays and MMR images that enabled the extraction of quantified information in terms of texture, intensity and shape and allowed to significantly improve a di agnosis of human organs. These techniques were significantly developed over the la st few years and combined feature detection and classification by using re gion based and artificial intelligence methods. By using growing databases of medical images processed with pattern recognition and classification t echniques, one can produce fast and consistent diagnosis of diseases based on the accumulated knowledge obtained from many other similar cases from the stored databases. The use of CCD cameras for astroph ysical instruments on the ground and space produce digitized images in va rious fields of astrophysics. In the past decade, many space and ground based instruments provide large numbers of digitized images of the ni ght skies and of the Sun, our closest star.

Table des matières

to Pattern Recognition and Classification in Medical and Astrophysical Images.- Image Standardization and Enhancement.- Intensity and Region-Based Feature Recognition in Solar Images.- Advanced Feature Recognition and Classification Using Artificial Intelligence Paradigms.- Feature Recognition and Classification Using Spectral Methods.

A propos de l'auteur

Valentina Zharkova is Chair of Applied Mathematics at the Department of Mathematics and Computing, University of Bradford, UK. Having obtained her M.Sc. degree from Taras Shevchenko National University of Kiev (NUK), Ukraine, and her Ph.D. degree from the Main Astronomical Observatory of the Ukrainian Academy of Sciences, she worked for NUK for 20 years. In 1992, she moved to the University of Glasgow as a Royal Society Research Fellow and in 2000 to the University of Bradford. She authored over 200 scientific publications including the key one in Nature (issue 6683, 1998) on the discovery of solar quakes, which was covered by media worldwide. Professor Zharkova is a member of the Royal Astronomical Society, the International Astronomical Union, the European Physical Society and of the Editorial Board of the Journal on Knowledge-based Engineering Systems (KES).

Résumé

During the past decade digital imaging has significantly progressed in all imaging areas ranging from medicine, pharmacy, chemistry, biology to astrophysics, meteorology and geophysics. The avalanche of digitized images produced a need for special techniques of processing and knowledge extraction from many digital images with minimal or even without human interaction. This has resulted in a new area in the digital processing called pattern recognition that becomes increasingly necessary owing to a growing number of images to be processed. The first applications of pattern recognition techniques were for the analysis of medical X rays and MMR images that enabled the extraction of quantified information in terms of texture, intensity and shape and allowed to significantly improve a di agnosis of human organs. These techniques were significantly developed over the la st few years and combined feature detection and classification by using re gion based and artificial intelligence methods. By using growing databases of medical images processed with pattern recognition and classification t echniques, one can produce fast and consistent diagnosis of diseases based on the accumulated knowledge obtained from many other similar cases from the stored databases. The use of CCD cameras for astroph ysical instruments on the ground and space produce digitized images in va rious fields of astrophysics. In the past decade, many space and ground based instruments provide large numbers of digitized images of the ni ght skies and of the Sun, our closest star.

Commentaires des clients

Aucune analyse n'a été rédigée sur cet article pour le moment. Sois le premier à donner ton avis et aide les autres utilisateurs à prendre leur décision d'achat.

Écris un commentaire

Super ou nul ? Donne ton propre avis.

Pour les messages à CeDe.ch, veuillez utiliser le formulaire de contact.

Il faut impérativement remplir les champs de saisie marqués d'une *.

En soumettant ce formulaire, tu acceptes notre déclaration de protection des données.