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Proceedings Paper

A robust pointer segmentation in biomedical images toward building a visual ontology for biomedical article retrieval
Author(s): Daekeun You; Matthew Simpson; Sameer Antani; Dina Demner-Fushman; George R. Thoma
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Paper Abstract

Pointers (arrows and symbols) are frequently used in biomedical images to highlight specific image regions of interest (ROIs) that are mentioned in figure captions and/or text discussion. Detection of pointers is the first step toward extracting relevant visual features from ROIs and combining them with textual descriptions for a multimodal (text and image) biomedical article retrieval system. Recently we developed a pointer recognition algorithm based on an edge-based pointer segmentation method, and subsequently reported improvements made on our initial approach involving the use of Active Shape Models (ASM) for pointer recognition and region growing-based method for pointer segmentation. These methods contributed to improving the recall of pointer recognition but not much to the precision. The method discussed in this article is our recent effort to improve the precision rate. Evaluation performed on two datasets and compared with other pointer segmentation methods show significantly improved precision and the highest F1 score.

Paper Details

Date Published: 4 February 2013
PDF: 9 pages
Proc. SPIE 8658, Document Recognition and Retrieval XX, 86580Q (4 February 2013); doi: 10.1117/12.2005934
Show Author Affiliations
Daekeun You, National Library of Medicine (United States)
Matthew Simpson, National Library of Medicine (United States)
Sameer Antani, National Library of Medicine (United States)
Dina Demner-Fushman, National Library of Medicine (United States)
George R. Thoma, National Library of Medicine (United States)

Published in SPIE Proceedings Vol. 8658:
Document Recognition and Retrieval XX
Richard Zanibbi; Bertrand Coüasnon, Editor(s)

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