If a picture is worth a thousand words, what is a trauma computerized tomography panel worth?

Aucar, John A.; Fernandez, Luis; Wagner‐Mann, Colette C.

doi:10.1016/j.amjsurg.2007.08.036

Cited by 16 publications

(11 citation statements)

References 18 publications

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“…In biomedical image retrieval [1]- [5], figures are often composed of multiple panels, each describing different methodologies, modalities or results, including the possibility of providing direct comparisons among them. 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].…”

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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“…This growth is particularly manifested in the scientific and medical domains. In the clinical domain, for example, Aucar, Fernandez, and Wagner‐Mann () report a trend of an increasing use of medical images. They examined medical images associated with trauma patients over a period of 4 years and observed that the number of radiographic studies increased by 82% during this time.…”

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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“…Advances in computed tomography (CT) imaging techniques over the last three decades have seen a commensurate increase in its use and importance in the initial assessment of the trauma patient. [1][2][3][4] Traditionally, CT scans have been used to further define injuries found or suspected during the primary and secondary surveys. [5][6][7] However, they are now also increasingly used as a primary imaging tool to screen for all non-extremity injuries in the trauma patient.…”

Section: Introductionmentioning

confidence: 99%