The Zebrafish DVD Exchange Project: A Bioinformatics Initiative

Cooper, Mark S.; Sommers-Herivel, Greg; Poage, Cara; McCarthy, Matthew B.; Crawford, Bryan D.; Phillips, Carey R.

doi:10.1016/s0091-679x(04)77024-7

Cited by 8 publications

(2 citation statements)

References 10 publications

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“…In this domain, authors report an increasing use of medical images [6], [7]. The average number of figures in reputable biomedical journals ranges from 6 to 31 [8], [9]. More importantly, according to [10]- [12], multipanel figures represent about 50% of the figures in the biomedical open access articles used for the imageCLEF (URL: http://www.imageclef.org) benchmark.…”

Section: A Motivationmentioning

confidence: 99%

Stitched Multipanel Biomedical Figure Separation

Santosh¹,

Thoma²

2015

2015 IEEE 28th International Symposium on Computer-Based Medical Systems

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We present a novel technique to separate subpanels from stitched multipanel figures appearing in biomedical research articles. Since such figures may comprise images from different imaging modalities, separating them is a critical first step for effective biomedical content-based image retrieval (CBIR). The method applies local line segment detection based on the graylevel pixel changes. It then applies a line vectorization process that connects prominent broken lines along the subpanel boundaries while eliminating insignificant line segments within the subpanels. We have validated our fully automatic technique on a subset of stitched multipanel biomedical figures extracted from articles within the Open Access subset of PubMed Central repository, and have achieved precision and recall of 81.22% and 85.08%, respectively.

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Section: A Motivationmentioning

confidence: 99%

Stitched Multipanel Biomedical Figure Separation

Santosh¹,

Thoma²

2015

2015 IEEE 28th International Symposium on Computer-Based Medical Systems

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“…Images are also abundantly used in scientific publications, particularly in the biomedical literature. The mean number of images per article in the leading biological journals ranges from 6.5 (Yu, ) to 31 (Cooper et al., ).…”

Section: Introductionmentioning

confidence: 99%

Image retrieval from scientific publications: Text and image content processing to separate multipanel figures

Аpostolova

You

Xue

et al. 2013

J Am Soc Inf Sci Tec

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Images contained in scientific publications are widely considered useful for educational and research purposes, and their accurate indexing is critical for efficient and effective retrieval. Such image retrieval is complicated by the fact that figures in the scientific literature often combine multiple individual subfigures (panels). Multipanel figures are in fact the predominant pattern in certain types of scientific publications. The goal of this work is to automatically segment multipanel figures-a necessary step for automatic semantic indexing and in the development of image retrieval systems targeting the scientific literature. We have developed a method that uses the image content as well as the associated figure caption to: (1) automatically detect panel boundaries; (2) detect panel labels in the images and convert them to text; and (3) detect the labels and textual descriptions of each panel within the captions. Our approach combines the output of imagecontent and text-based processing steps to split the multipanel figures into individual subfigures and assign to each subfigure its corresponding section of the caption. The developed system achieved precision of 81% and recall of 73% on the task of automatic segmentation of multipanel figures.

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Automatic Compound Figure Separation in Scientific Articles: A Study of Edge Map and Its Role for Stitched Panel Boundary Detection

Aafaque

Santosh

2017

Communications in Computer and Information Science

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The Zebrafish DVD Exchange Project: A Bioinformatics Initiative

Cited by 8 publications

References 10 publications

Stitched Multipanel Biomedical Figure Separation

Stitched Multipanel Biomedical Figure Separation

Image retrieval from scientific publications: Text and image content processing to separate multipanel figures

Automatic Compound Figure Separation in Scientific Articles: A Study of Edge Map and Its Role for Stitched Panel Boundary Detection

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