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Medical-Image Retrieval Based on Knowledge-Assisted Text and Image Indexing

C. Lacoste, Joo-Hwee Lim, J.-P. Chevallet, D.T.H. Le
2007 IEEE transactions on circuits and systems for video technology (Print)  
We propose a structured learning framework based on support vector machines to facilitate modular design and learning of medical semantics from images.  ...  First, a simple fusion of the textual and visual retrieval approaches is proposed, improving significantly the retrieval results of both text and image retrieval.  ...  The authors would also like to thank the ImageCLEFmed organizers for making available a large medical image dataset to evaluate our algorithms, and, especially, H. Mueller, W. Hersh, and T.  ... 
doi:10.1109/tcsvt.2007.897114 fatcat:s3phy77d3nhazfgubsyqshzaqu

IPAL Knowledge-based Medical Image Retrieval in ImageCLEFmed 2006

Caroline Lacoste, Jean-Pierre Chevallet, Joo-Hwee Lim, Xiong Wei, Daniel Racoceanu, Diem Thi Hoang Le, Roxana Teodorescu, Nicolas Vuillemenot
2006 Conference and Labs of the Evaluation Forum  
For images, this knowledge is in semantic features that are learned from examples within structured learning framework. We propose to represent both image and text using UMLS concepts.  ...  The use of UMLS concepts allows the system to work at a higher semantic level and to standardize the semantic index of medical data, facilitating the communication between visual end textual indexing and  ...  filtering. 3 Visual Retrieval UMLS-based visual indexing and retrieval In order to manage large and complex sets of visual entities in the medical domain, we developed a structured learning framework  ... 
dblp:conf/clef/LacosteCLWRLTV06 fatcat:ka7vj5s5wzhxtndxjt64hxb6sy

Toward translational incremental similarity-based reasoning in breast cancer grading

Adina E. Tutac, Daniel Racoceanu, Wee-Keng Leow, Henning Müller, Thomas Putti, Vladimir Cretu, Nico Karssemeijer, Maryellen L. Giger
2009 Medical Imaging 2009: Computer-Aided Diagnosis  
structure of the knowledge (CBR), image usage to retrieve similar cases (CBIR), similarity concept (central for both paradigms).  ...  For this purpose, three major axes are explored: the indexing, the cases retrieval and the search refinement, applied to Breast Cancer Grading (BCG), a powerful breast cancer prognosis exam.  ...  ACKNOWLEDGEMENTS This project is partially supported by the ONCO-MEDIA 2 project and MMedWeb 3  ... 
doi:10.1117/12.813731 dblp:conf/micad/TutacRLMPC09 fatcat:tkysogzkvfgvrkwcbihuvml2oq

A Semantic Fusion Approach Between Medical Images and Reports Using UMLS [chapter]

Daniel Racoceanu, Caroline Lacoste, Roxana Teodorescu, Nicolas Vuillemenot
2006 Lecture Notes in Computer Science  
In this paper, we present our first results concerning a medical image retrieval approach using a semantic medical image and report indexing within a fusion framework, based on the Unified Medical Language  ...  We propose a structured learning framework based on Support Vector Machines to facilitate modular design and extract medical semantics from images.  ...  The main idea of our approach is to use the medical rapport and medical image conceptual and/or visual-concept indexing in order to build an homogeneous high level fusion approach for improve the retrieval  ... 
doi:10.1007/11880592_35 fatcat:tozgl35tkzhilmgoy72lu6kvui

Convolution Index based Unsupervised Label Procedure for Efficient Medical Image Exploration

Medical imaging is a forceful idea of various medicinal ideas i.e. malignant growth and other related infections, present days; various kinds of therapeutic pictures are caught and saved in computerized  ...  Confronting this kind of huge volume of picture information with various sorts of picture modalities, it is critical to execute effective content based image retrieval (CBIR) for restorative research focuses  ...  retrieval, medical image, unsupervised learning, computed tomography and Convolution neural network.  ... 
doi:10.35940/ijitee.l3707.1081219 fatcat:2r7ujz3u4fbepodzchedoiqbyu

Online Retrieval and Indexing of Images using Multi Feature Vectors

We also present the pros and cons of our novel framework for online retrieval and indexing of images using multi feature vectors.  ...  The cutting edge technologies have paved way for sophisticated and feature rich image processing in medical field using colour tomography and medical resonance imaging.  ...  R Cornet et al [8] , proposed an indexing method for medical images using hierarchical cluster structure and the LBP operator.  ... 
doi:10.35940/ijitee.k1104.09811s19 fatcat:lqteli47grdclp3r567eu4r7bq

VisMed: A Visual Vocabulary Approach for Medical Image Indexing and Retrieval [chapter]

Joo-Hwee Lim, Jean-Pierre Chevallet
2005 Lecture Notes in Computer Science  
To facilitate automatic indexing and retrieval of large medical image databases, we propose a structured framework for designing and learning vocabularies of meaningful medical terms associated with visual  ...  Voluminous medical images are generated daily. They are critical assets for medical diagnosis, research, and teaching.  ...  Acknowledgments We would like to thank Mun-Kew Leong and Changsheng Xu for their feedback on the paper. We also thank T. Joachims for making his SV M light software available.  ... 
doi:10.1007/11562382_7 fatcat:q6vp66lq3jbftjgmnq6sd25jby

Image Retrieval Using Mixture Models and EM Algorithm [chapter]

Micheline Najjar, Christophe Ambroise, Jean Pierre Cocquerez
2003 Lecture Notes in Computer Science  
This paper presents an original system for interactive content-based image retrieval (CBIR). A novel approach for searching by similarity is introduced.  ...  The presented retrieval system is evaluated and validated using a medical image database and the Washington University heterogeneous database (ANN).  ...  In this paper, we present a general image retrieval system based on a semi-supervised learning approach.  ... 
doi:10.1007/3-540-45103-x_146 fatcat:n4iz3vstbjflxiif3cn5yy36qi

Large-scale retrieval for medical image analytics: A comprehensive review

Zhongyu Li, Xiaofan Zhang, Henning Müller, Shaoting Zhang
2018 Medical Image Analysis  
In this paper, we review state-of-the-art approaches for large-scale medical image analysis, which are mainly based on recent advances in computer vision, machine learning and information retrieval.  ...  On the basis of existing work, we introduce the evaluation protocols and multiple applications of large-scale medical image retrieval, with a variety of exploratory and diagnostic scenarios.  ...  (Cao et al., 2014) 475 developed a multimodal approach for medical image retrieval that is based on 476 deep Boltzmann machines.  ... 
doi:10.1016/ pmid:29031831 fatcat:s6jnxawnongufgdngpjeifv3vm

Development of an Image Retrieval Model for Biomedical Image Databases [chapter]

Achimugu Philip, Babajide Afolabi, Adeniran Oluwaranti, Oluwagbemi Oluwatolani
2011 Efficient Decision Support Systems - Practice and Challenges in Biomedical Related Domain  
Image processing a is very important subject, and finds itself in such fields as photography, satellite imaging, medical imaging, and image compression, to name but a few.  ...  Image retrieval, popularly referred to as content-based image retrieval is an emerging technology that allows a user to retrieve relevant images in an effective and efficient manner.  ...  Conclusion In this research, we have described a method for storage, retrieval and manipulation of digital medical images by content.  ... 
doi:10.5772/16875 fatcat:c4skyp4y55f3hmkv3ouv4jzoum

Texture Bags: Anomaly Retrieval in Medical Images Based on Local 3D-Texture Similarity [chapter]

Andreas Burner, René Donner, Marius Mayerhoefer, Markus Holzer, Franz Kainberger, Georg Langs
2012 Lecture Notes in Computer Science  
For retrieval, our method computes a texture histogram of a query region marked by a physician, and searches for similar bags via diffusion distance.  ...  In this paper, we present an effective method for content-based image retrieval (CBIR) of anomalies in medical imaging data, based on similarity of local 3D texture.  ...  Aim In this work we apply unsupervised learning to medical image retrieval.  ... 
doi:10.1007/978-3-642-28460-1_11 fatcat:dxh4lgfx7bh7vnsykeretd6ara

Content-based image retrieval for large biomedical image archives

Sameer Antani, L Rodney Long, George R Thoma
2004 Studies in Health Technology and Informatics  
Content-Based Image Retrieval (CBIR) has been a topic of research interest for nearly a decade. Approaches to date use image features for describing content.  ...  Our research focuses on developing techniques for hybrid text/image query-retrieval from the survey text and image data.  ...  As an initial step, however, we have adopted this approach [11] for organizing indexing trees and optimizing the node structure with the spine x-ray images shapes.  ... 
pmid:15360928 fatcat:ujuwbjvusbfrplcfio2men7qjm

Content-Based Medical Image Retrieval: A Survey of Applications to Multidimensional and Multimodality Data

Ashnil Kumar, Jinman Kim, Weidong Cai, Michael Fulham, Dagan Feng
2013 Journal of digital imaging  
In this paper, we present a review of state-of-the-art medical CBIR approaches in five main categories: two-dimensional image retrieval, retrieval of images with three or more dimensions, the use of nonimage  ...  We use these categories as a framework for discussing the state of the art, focusing on the characteristics and modalities of the information used during medical image retrieval.  ...  Acknowledgments We are grateful to our collaborators at the Royal Prince Alfred Hospital, Sydney, Australia for their direct and indirect contributions to this work.  ... 
doi:10.1007/s10278-013-9619-2 pmid:23846532 pmcid:PMC3824925 fatcat:5hasvmf7uncjtkpip4w4keea5m

An Approach toward the Efficient Indexing and Retrieval on Medical X-Ray Images

Sumathi Ganesan, T. S. Subashini
2013 International Journal of Computer Applications  
This paper proposes a system for content based image retrieval of X-ray images.The six classes of X-ray images used for this work are from the IRMA ImageCLEFmed 2008 database.  ...  With rapid advances in digital imaging modalities, the use of CBIR to search for the clinically relevant and visually similar medical images is highly felt nowadays.  ...  INDEXING Once image features were extracted and classified, they should be indexed and matched against each other for retrieval.  ... 
doi:10.5120/13297-0730 fatcat:zsf5r3gilrhsneuldxdz5cdtyy

Medical Image Retrieval: Applications and Resources

Henning Müller
2020 Proceedings of the 2020 International Conference on Multimedia Retrieval  
Much knowledge is stored in these medical archives of images and other clinical information and content-based medical image retrieval has from the start aimed at making such knowledge accessible using  ...  Most images are used only in the context of a single patient and a single time point, besides a few images that are used for publications or in teaching.  ...  to the current multimodal systems that can index many types of images in large quantities and use deep learning as a basis for the tools [1, 2, 3, 4] .  ... 
doi:10.1145/3372278.3390668 dblp:conf/mir/Muller20 fatcat:mvg2xl6tqbhcxixrgnjmqhau6y
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