A knowledge-based database system for visual rating of fMRI activation patterns for brain language networks
Conference
Guillen, MR, Adjouadi, M, Bernal, B et al. (2009). A knowledge-based database system for visual rating of fMRI activation patterns for brain language networks
. 1-6. 10.1145/1565799.1565801
Guillen, MR, Adjouadi, M, Bernal, B et al. (2009). A knowledge-based database system for visual rating of fMRI activation patterns for brain language networks
. 1-6. 10.1145/1565799.1565801
This paper describes a novel multimedia tool to facilitate visual assessment of Functional Magnetic Resonance Imaging (fMRI) activation patterns by human experts. A great effort is placed by radiologists and neurologists to present a consistent methodology to provide assessment for brain activation map images. Since each radiologist has his own way to perform the visual analysis on the images and present the findings, rating a large and heterogeneous group of images is a hard task. Although this tool is focused on assessing fMRI activation patterns related to brain language network paradigms, the tool can be extended to other brain activation maps, such as motor, reading, and working memory. Moreover, the same tool can be used for assessing images acquired using different recording modalities as long as these images are saved in standard image formats such as JPEG, BMP, or PNG. The use of this tool is independent of the methodology used to generate the brain activation map, which can be done using specialized software tools such as Statistical Parametric Mapping (SPM) or fMRI Software Library (FSL). The main benefits of using this tool for brain activation image scoring are the systematic approach for rating the activation maps, the automatic descriptive statistics applied to the results and the reduction of assessment time from several minutes to seconds. For each study, the proposed system presents the activation pattern image, based on which the rater is asked to indicate the level and type of activation observed in general, and in specific on the following areas: frontal, temporal, and supplemental motor area. Copyright 2009 ACM.
