NDLI: Detecting Figure-Panel Labels in Medical Journal Articles Using MRF

Content Provider	IEEE Xplore Digital Library
Author	Daekeun You Antani, S. Demner-Fushman, D. Govindaraju, V. Thoma, G.R.
Copyright Year	2011
Abstract	We present a method for figure-panel (subfigure) label detection and recognition in multi-panel figures extracted from biomedical articles. Figures in biomedical articles often comprise several subfigures that are identified by superimposed panel labels ('A', 'B', ...) which are referenced in the figure caption and discussion in the article body. Splitting such multi-panel figures into individual subfigures is a necessary step for improved multimodal biomedical information retrieval. Prior to feature extraction for indexing and retrieval of biomedical figures it is necessary to classify image content in each subfigure by its modality (X-ray, MRI, CT, etc.) and other relevant criteria. Subfigure labels are valuable in associating individual panels with relevant text in captions and discussion. We propose a 4-step panel label detection method based on Markov Random Field (MRF). Experiments on 515 multi-panel figures and analysis of the results show promising results. We present the successes and identify critical challenges.
Starting Page	967
Ending Page	971
File Size	2528657
Page Count	5
File Format	PDF
ISBN	9781457713507
ISSN	15205363
e-ISBN	9780769545202
DOI	10.1109/ICDAR.2011.196
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optical character recognition software Biomedical imaging Noise Feature extraction Character recognition Nickel Markov random fields image classification image-text detection Markov Random Field belief propagation OCR Neural network image binarization CBIR
Content Type	Text
Resource Type	Article

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