Image approach towards document mining in neuroscientific publications

Authors:
Jayaprakash Rajasekharan;Ulrike Scharfenberger;Nicolau Gonçalves;Ricardo Vigário
Affiliations:
Department of Signal Processing and Acoustics, Aalto University School of Science and Technology, Finland;Department of Computer Engineering, Eberhard-Karls-University Tübingen, Germany;Adaptive Informatics Research Centre, Aalto University School of Science and Technology, Finland;Adaptive Informatics Research Centre, Aalto University School of Science and Technology, Finland
Venue:
IDA'10 Proceedings of the 9th international conference on Advances in Intelligent Data Analysis
Year:
2010

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Abstract

This paper addresses the issue of a content-based information retrieval system that works on fMRI images from neuroscientific journal publications. We present a general framework for automatic extraction, characterisation and classification of fMRI images, based on their functional properties. The proposed method identifies the section of each of those images, by morphological processing, and estimates the coordinates of the brain activated regions, in relation to a standard reference template using locality preserving projections. Those regions are then segmented, and their physical and geometrical properties evaluated. We formulate a feature vector based on these characteristics, and cluster the images and corresponding journal publications using self organizing maps.