Proceedings ArticleDOI
Detecting Figure-Panel Labels in Medical Journal Articles Using MRF
Daekeun You,Sameer Antani,Dina Demner-Fushman,Venu Govindaraju,George R. Thoma +4 more
- pp 967-971
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TLDR
A 4-step panel label detection method based on Markov Random Field (MRF) is proposed and experiments on 515 multi-panel figures show promising results and critical challenges are identified.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.read more
Citations
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Proceedings Article
Image Processing
TL;DR: The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images.
Journal ArticleDOI
Design and Development of a Multimodal Biomedical Information Retrieval System
TL;DR: Techniques and tools from the fields of natural language processing, information retrieval, and content-based image retrieval allow the development of building blocks for advanced information services.
Journal ArticleDOI
Image retrieval from scientific publications: Text and image content processing to separate multipanel figures
TL;DR: This work has developed a method that uses the image content as well as the associated figure caption to automatically segment multipanel figures, a necessary step for automatic semantic indexing and in the development of image retrieval systems targeting the scientific literature.
Proceedings ArticleDOI
Separating compound figures in journal articles to allow for subfigure classification
Ajad Chhatkuli,Antonio Foncubierta-Rodríguez,Dimitrios Markonis,Fabrice Meriaudeau,Henning Müller +4 more
TL;DR: In this paper, a technique of compound figure separation is proposed and implemented based on systematic detection and analysis of uniform space gaps, which is evaluated on a dataset of journal figures of the open access literature that was created for the ImageCLEF 2012 benchmark.
Journal ArticleDOI
A framework for biomedical figure segmentation towards image-based document retrieval
Luis D. Lopez,Jingyi Yu,Cecilia N. Arighi,Cecilia N. Arighi,Catalina O. Tudor,Manabu Torii,Hongzhan Huang,Hongzhan Huang,K. Vijay-Shanker,Cathy H. Wu,Cathy H. Wu +10 more
TL;DR: A robust solution for automatically identifying and segmenting unimodal panels from a multimodal figure by robustly harvesting figure-caption pairs from biomedical articles is described and a web-based interface is developed to allow for efficient retrieval of information.
References
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Book
Image Processing: Analysis and Machine Vision
TL;DR: The digitized image and its properties are studied, including shape representation and description, and linear discrete image transforms, and texture analysis.
Proceedings Article
Image Processing
TL;DR: The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images.
Book
Markov Random Field Modeling in Image Analysis
TL;DR: This detailed and thoroughly enhanced third edition presents a comprehensive study / reference to theories, methodologies and recent developments in solving computer vision problems based on MRFs, statistics and optimisation.
Journal ArticleDOI
A lexicon driven approach to handwritten word recognition for real-time applications
Gyeonghwan Kim,Venu Govindaraju +1 more
TL;DR: Experimental results prove that the approach using the variable duration outperforms the method using fixed duration in terms of both accuracy and speed.
Book ChapterDOI
Overview of the CLEF 2009 medical image retrieval track
Henning Müller,Jayashree Kalpathy-Cramer,Ivan Eggel,Steven Bedrick,Saïd Radhouani,Brian Bakke,Charles E. Kahn,William R. Hersh +7 more
TL;DR: The ImageCLEF medical retrieval task as discussed by the authors was the first to include case-based topics as an exploratory task, which were designed to be closer to the clinical workflow, as clinicians often seek information about patient cases using incomplete information consisting of symptoms, findings and a set of images.