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Combining Global Features within a Nearest Neighbor Classifier for Content-based Retrieval of Medical Images

Mark Oliver Güld, Christian Thies, Benedikt Fischer, Thomas Martin Lehmann
2006 Conference and Labs of the Evaluation Forum  
A combination of several classifiers using global features for the content description of medical images is proposed.  ...  When applied in the medical retrieval task, this combination of classifiers yields a mean average precision (MAP) of 0.0172, which is rank 11 of 11 submitted runs for automatic, visual only systems.  ...  Nearest-Neighbor Classifier To obtain a decision q → c ∈ {1 . . . C} for a query image q, a nearest neighbor classifier evaluating k nearest neighbors according to a distance measure is used (k-NN).  ... 
dblp:conf/clef/GuldTFL06 fatcat:k5ykwr4odvcnrdzxgmjdx7imi4

Similarity of Medical Images Computed from Global Feature Vectors for Content-Based Retrieval [chapter]

Thomas M. Lehmann, Mark O. Güld, Daniel Keysers, Thomas Deselaers, Henning Schubert, Berthold Wein, Klaus Spitzer
2004 Lecture Notes in Computer Science  
Global features describe the image content by a small number of numerical values, which are usually combined into a vector of less than 1,024 components.  ...  A maximum classification accuracy of 86% was obtained using the winner-takes-all rule and a one nearest neighbor classifier.  ...  In summary, the figures presented prove that global image features are suitable for content-based retrieval of medical images.  ... 
doi:10.1007/978-3-540-30133-2_131 fatcat:3fxjsljq2fdqhmo6mnvikhts5a

Classification of Medical Images Using Local Representations [chapter]

Roberto Paredes, Daniel Keysers, Thomas M. Lehmann, Berthold Wein, Hermann Ney, Enrique Vidal
2002 Bildverarbeitung für die Medizin 2002  
This approach is combined with a fast approximate -nearest neighbor technique and yields state-of-the-art results on a medical image database of 1617 images.  ...  In medical image retrieval, the images are usually subject to a large range of variability.  ...  Introduction Recently, research within the field of content-based medical image retrieval has attracted a lot of attention.  ... 
doi:10.1007/978-3-642-55983-9_39 fatcat:opte3dpnszbihcvmns3bnbchbm

Comparison of global features for categorization of medical images

Mark O. Gueld, Daniel Keysers, Thomas Deselaers, Marcel Leisten, Henning Schubert, Hermann Ney, Thomas M. Lehmann, Osman M. Ratib, H. K. Huang
2004 Medical Imaging 2004: PACS and Imaging Informatics  
This is sufficient for most applications in content-based image retrieval.  ...  The classification is done using a nearest neighbor classifier with various distance measures as well as the automatic combination of classifier results.  ...  Considering image categorization as initial step for image retrieval based on local features, the correct image category should be within the five or ten nearest neighbors.  ... 
doi:10.1117/12.535914 fatcat:mnjotzlbxbejlirokmlc3ic254

Content-Based Retrieval and Classification of Ultrasound Medical Images of Ovarian Cysts [chapter]

Abu Sayeed Md. Sohail, Prabir Bhattacharya, Sudhir P. Mudur, Srinivasan Krishnamurthy, Lucy Gilbert
2010 Lecture Notes in Computer Science  
This paper presents a combined method of content-based retrieval and classification of ultrasound medical images representing three types of ovarian cysts: Simple Cyst, Endometrioma, and Teratoma.  ...  Combination of histogram moments and Gray Level Co-Occurrence Matrix (GLCM) based statistical texture descriptors has been proposed as the features for retrieving and classifying ultrasound images.  ...  A large number of propositions have already been made for content-based retrieval of medical images including radiology images, X-ray images, CT images of lung, dermatology images, MRI images of heart  ... 
doi:10.1007/978-3-642-12159-3_16 fatcat:zsuulhzkujbzpofuwu44mmbbtu

Features Advances to Automatically Find Images for Application to Clinical Decision Support

Ronald Stanley
2016 Medical Research Archives  
Filtering through ever increasing sources of information to find relevant information for clinical decisions is a challenging task for clinicians.  ...  In biomedical publications, there are a variety of items that can provide evidence to aid the decision making process.  ...  Nearest Neighbor Classifier The nearest neighbor classifier was used as follows for the two experiments.  ... 
doi:10.18103/mra.v4i7.761 fatcat:riwsgtci3fhtphodl7droceixu

Content-based Image Retrieval in Medical Applications

M. O. Güld, C. Thies, B. Fischer, K. Spitzer, D. Keysers, H. Ney, M. Kohnen, H. Schubert, B. B. Wein, T. M. Lehmann
2004 Methods of Information in Medicine  
to a variety of applications for content-based image retrieval in medicine.  ...  The proposed architecture is suitable for content-based image retrieval in medical applications.  ...  We are grateful to Tim Dwyer, Department of Computer Science, University of Melbourne, Australia, for providing the WilmaScope 3D graph visualization system (http://www.wilmascope.org) used to display  ... 
doi:10.1055/s-0038-1633877 pmid:15472746 fatcat:ku4ccdhh7vflrnrm2qehb6rphu

Medical Image Retrieval Using Empirical Mode Decomposition with Deep Convolutional Neural Network

Shaomin Zhang, Lijia Zhi, Tao Zhou, Lin Gu
2020 BioMed Research International  
Content-based medical image retrieval (CBMIR) systems attempt to search medical image database to narrow the semantic gap in medical image analysis.  ...  In this paper, we propose a deep convolutional neural network- (CNN-) based framework to learn concise feature vector for medical image retrieval.  ...  The learned concise feature vectors are suitable for both classification-based and nearest-neighbor similarity-based medical image retrieval and show the great potential to handle large-scale medical image  ... 
doi:10.1155/2020/6687733 pmid:33426062 pmcid:PMC7781707 fatcat:rgn4jwke2vdsthadbla35pl754

X-Ray Image Classification and Retrieval Using Ensemble Combination of Visual Descriptors [chapter]

JeongHee Shim, KiHee Park, ByoungChul Ko, JaeYeal Nam
2009 Lecture Notes in Computer Science  
In this paper, we propose a novel algorithm for the efficient classification and retrieval of medical images, especially X-ray images.  ...  From the membership scores of H-CSD and EHD, two membership scores are combined as one ensemble feature and it is used for similarity matching of our retrieval system, MISS (Medical Information Searching  ...  This work was supported by grant RTI04-01-01 from the Regional Technology Innovation Program of the Korean Ministry of Commerce, Industry, and Energy (MOCIE).  ... 
doi:10.1007/978-3-540-92957-4_64 fatcat:cbrrz5vwpjfbfg6bzd3vj75l64

An intelligent content-based image retrieval system for clinical decision support in brain tumor diagnosis

Megha P. Arakeri, G. Ram Mohana Reddy
2013 International Journal of Multimedia Information Retrieval  
Accordingly in this paper, we propose an intelligent content-based image retrieval (CBIR) system which retrieves similar pathology bearing magnetic resonance (MR) images of the brain from a medical database  ...  A single feature vector will not perform well for finding similar images in the medical domain as images within the same disease class differ by severity, density and other such factors.  ...  Acknowledgments The authors wish to thank the anonymous reviewers for the useful and valuable suggestions.  ... 
doi:10.1007/s13735-013-0037-5 fatcat:liqlh7jrmjbmfnfe7qrosf7b7a

Content-Based Queries on the CasImage Database Within the IRMA Framework [chapter]

Christian Thies, Mark Oliver Güld, Benedikt Fischer, Thomas M. Lehmann
2005 Lecture Notes in Computer Science  
It supports the loop of estimating a combination of distance measures, parameter adaption and result visualization, which is characteristic if an image retrieval application is used for varying data corpora  ...  Image retrieval in medical applications (IRMA) is a framework that strictly separates data administration and application logic.  ...  Here the retrieval task is the detection of the nearest-neighbors to the query image in the image database. This is based on the similarity of abstract representations of images in a feature space.  ... 
doi:10.1007/11519645_76 fatcat:5hqjncmp3rcsnmkjn7d3u3qz6m

Natural language processing versus content-based image analysis for medical document retrieval

Aurélie Névéol, Thomas M. Deserno, Stéfan J. Darmoni, Mark Oliver Güld, Alan R. Aronson
2009 Journal of the American Society for Information Science and Technology  
The performance of text-based and image-based access, as well as combined document features, is compared. Image analysis proves more adequate for both the indexing and retrieval of the images.  ...  Content-based image analysis and natural language processing techniques are applied individually and combined for multimodal document analysis.  ...  Acknowledgments This research was supported in part by an appointment of A. Névéol to the Lister Hill Center Fellows Program and an appointment of T.M.  ... 
doi:10.1002/asi.20955 pmid:19633735 pmcid:PMC2714909 fatcat:3riwtj6n6zc6xk32szlsk5zkaq

Effectiveness of global features for automatic medical image classification and retrieval – The experiences of OHSU at ImageCLEFmed

Jayashree Kalpathy-Cramer, William Hersh
2008 Pattern Recognition Letters  
The goal of the automatic annotation task was to classify 1000 test images based on the Image Retrieval in Medical Applications (IRMA) code, given a set of 10,000 training images.  ...  A multitude of classifiers including k-nearest neighbors, two-level neural networks, support vector machines, and maximum likelihood classifiers were evaluated.  ...  Acknowledgments We acknowledge the support of NLM Training Grant 1T15 LM009461 and NSF Grant ITR-0325160. Kalpathy-Cramer and Hersh  ... 
doi:10.1016/j.patrec.2008.05.013 pmid:19884953 pmcid:PMC2598732 fatcat:v2my5yhr2nbcdc2radrbw2jota

Ambiguous Proximity Distribution [chapter]

Quanquan Wang, Yongping Li
2014 Lecture Notes in Computer Science  
The experiments are conducted on both classification and retrieval of medical image data sets.  ...  In this paper, we investigate the soft assignment of visual words to image features for proximity distribution.  ...  This work presents a novel content-based image retrieval system, which is based on the Visual Words (VW) framework.  ... 
doi:10.1007/978-3-319-09339-0_42 fatcat:rvll5qlzoneudkjaiz7lcqyjge

Content-Based Image Retrieval for Carotid Plaque Ultrasound Images

C.I. Christodoulou, C.S. Pattichis, E.C. Kyriacou, M. Pantziaris, A.N. Nicolaides
2005 Zenodo  
In this work a content-based image retrieval system is implemented using texture, histogram, shape and correlogram features and the SOM neural and the KNN statistical classifiers reaching a correct retrieval  ...  The retrieval of similar medical images from a database of digital images with a known symptom outcome can be very useful for a better assessment of disease and treatment.  ...  Imaging of the Carotid Artery (TALOS) of the Research Promotion Foundation of Cyprus.  ... 
doi:10.5281/zenodo.2574048 fatcat:p2jsm2qwg5gqrnd75v67glgyzq
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