NDLI: Interactive cross and multimodal biomedical image retrieval based on automatic region-of-interest (ROI) identification and classification

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Interactive cross and multimodal biomedical image retrieval based on automatic region-of-interest (ROI) identification and classification

Content Provider	Springer Nature Link
Author	Thoma, George R. Antani, Sameer K. Rahman, Md Mahmudur You, Daekeun Demner Fushman, Dina Simpson, Matthew S.
Copyright Year	2014
Abstract	In biomedical articles, authors often use annotation markers such as arrows, letters, or symbols overlaid on figures and illustrations to highlight ROIs. These annotations are then referenced and correlated with concepts in the caption text or figure citations in the article text. This association creates a bridge between the visual characteristics of important regions within an image and their semantic interpretation. Identifying these assists in extracting ROIs that are likely to be highly relevant to the discussion in the article text. The aim of this work is to perform semantic search without knowing the concept keyword or the specific name of the visual pattern or appearance. We consider the problem of cross and multimodal retrieval of images from articles which contains components of text and images. Our proposed method localizes and recognizes the annotations by utilizing a combination of rule-based and statistical image processing techniques. The image regions are then annotated for classification using biomedical concepts obtained from a glossary of imaging terms. Similar automatic ROI extraction can be applied to query images, or to interactively mark an ROI. As a result, visual characteristics of the ROIs can be mapped to text concepts and then used to search image captions. In addition, the system can toggle the search process from purely perceptual to a conceptual one (crossmodal) based on utilizing user feedback or integrate both perceptual and conceptual search in a multimodal search process. The hypothesis, that such approaches would improve biomedical image retrieval, was validated through experiments on a biomedical article dataset of thoracic CT scans.
Starting Page	131
Ending Page	146
Page Count	16
File Format	PDF
ISSN	21926611
Journal	International Journal of Multimedia Information Retrieval
Volume Number	3
Issue Number	3
e-ISSN	2192662X
Language	English
Publisher	Springer London
Publisher Date	2014-05-13
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Relevance feedback Biomedical image annotation Cross-modal retrieval Multimodal biomedical information retrieval Image overlay extraction Classification Information Storage and Retrieval Data Mining and Knowledge Discovery Image Processing and Computer Vision Computer Science Information Systems Applications (incl. Internet) Multimedia Information Systems
Content Type	Text
Resource Type	Article
Subject	Library and Information Sciences Information Systems Media Technology

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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