title: Mining biomedical images towards valuable information retrieval in biomedical and life sciences.
abstract: Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries.
authors.affiliation: The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA zeeshan.ahmed@jax.org.
authors.forename: Zeeshan
authors.initials: Z
authors.lastname: Ahmed
authors.affiliation: The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
authors.forename: Saman
authors.initials: S
authors.lastname: Zeeshan
authors.affiliation: Department of Bioinformatics, Biocenter, University of Wuerzburg, Wuerzburg, Germany EMBL, Computational Biology and Structures Program, Heidelberg, Germany zeeshan.ahmed@jax.org.
authors.forename: Thomas
authors.initials: T
authors.lastname: Dandekar
mesh_terms: D000818:Animals; D057225:Data Mining / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D009323:Natural Language Processing; D012984:Software