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X-ray Categorization and Retrieval on the Organ and Pathology Level, Using Patch-Based Visual Words

Uri Avni, Hayit Greenspan, Eli Konen, Michal Sharon, Jacob Goldberger
2011 IEEE Transactions on Medical Imaging  
The methodology is based on local patch representation of the image content, using a "bag of visual words" approach.  ...  In addition to organ-level discrimination, we show an application to pathology-level categorization of chest x-ray data, the most popular examination in radiology.  ...  X-ray Categorization and Retrieval on the Organ and Pathology Level, Using Patch-Based Visual Words Uri Avni, Hayit Greenspan, Eli Konen , Michal Sharon, Jacob Goldberger Abstract-In this study we present  ... 
doi:10.1109/tmi.2010.2095026 pmid:21118769 fatcat:gseqpdx2zfc4rdkmyysal7dqfm

X-ray image categorization and retrieval using patch-based visualwords representation

Uri Avni, Hayit Greenspan, Michal Sharon, Eli Konen, Jacob Goldberger
2009 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro  
In addition to organ-level discrimination, we show initial results of pathology-level categorization of chest x-ray data.  ...  In a recent international competition the system was ranked as one of the top schemes in discriminating orientation and body regions in x-ray images, and in medical visual retrieval.  ...  Categorization on the pathology level Image similarity-based categorization and retrieval becomes of clinical value once the task involves a diagnostic-level categorization, such as healthy vs pathology  ... 
doi:10.1109/isbi.2009.5193056 dblp:conf/isbi/AvniGSKG09 fatcat:uolonl2mhbcudb5xgzeqsyz67m

X-ray Categorization and Spatial Localization of Chest Pathologies [chapter]

Uri Avni, Hayit Greenspan, Jacob Goldberger
2011 Lecture Notes in Computer Science  
We show an application to pathology-level categorization of chest x-ray data, the most popular examination in radiology.  ...  In this study we present an efficient image categorization system for medical image databases utilizing a local patch representation based on both content and location.  ...  The authors wish to thank Dr. Eli Konen and Dr.  ... 
doi:10.1007/978-3-642-23626-6_25 fatcat:cnmmljhsevdshlbm4czezkyela

Biomedical image representation and classification using an entropy weighted probabilistic concept feature space

Md Mahmudur Rahman, Sameer K. Antani, Dinna Demner-Fushman, George R. Thoma, Maria Y. Law, Tessa S. Cook
2014 Medical Imaging 2014: PACS and Imaging Informatics: Next Generation and Innovations  
low level and visual word-based approaches.  ...  Furthermore, importance of concepts is measured as Shannon entropy based on pixel values of image patches and used to refine the feature vector to overcome the limitation of the "TF-IDF"based weighting  ...  We would like to thank the CLEF 3 organizers for making the database available for the experiments.  ... 
doi:10.1117/12.2043911 fatcat:mz4iznlqp5drjivrevs7u4am44

Table of Contents

2011 IEEE Transactions on Medical Imaging  
Tosun and C. Gunduz-Demir 721 X-ray Categorization and Retrieval on the Organ and Pathology Level, Using Patch-Based Visual Words .................  ...  X. Wu, X. Dou, A. Wahle, and M.  ... 
doi:10.1109/tmi.2011.2119271 fatcat:klhzctp3onbhbogbthbp542pei

Biomedical image representation approach using visualness and spatial information in a concept feature space for interactive region-of-interest-based retrieval

Md. Mahmudur Rahman, Sameer K. Antani, Dina Demner-Fushman, George R. Thoma
2015 Journal of Medical Imaging  
Further, the visual significance (e.g., visualness) of concepts is measured as the Shannon entropy of pixel values in image patches and is used to refine the feature vector.  ...  Further, a spatial verification step is used as a postprocessing step to improve retrieval results based on location information.  ...  We thank the Image-CLEFmed 23 organizers for making the data set available for the experiments.  ... 
doi:10.1117/1.jmi.2.4.046502 pmid:26730398 pmcid:PMC4695659 fatcat:6yx6dxqzszgirhzyzfkhixaxle

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)  
Two fusion approaches are developed to improve textual retrieval using the UMLS-based image indexing.  ...  First, a simple fusion of the textual and visual retrieval approaches is proposed, improving significantly the retrieval results of both text and image retrieval.  ...  Deselaers for the organization of image retrieval from medical collections. Finally, they would also like to thank T. Joachims for making his software available.  ... 
doi:10.1109/tcsvt.2007.897114 fatcat:s3phy77d3nhazfgubsyqshzaqu

Quantitative Morphometry for Osteochondral Tissues Using Second Harmonic Generation Microscopy and Image Texture Information

Takashi Saitou, Hiroshi Kiyomatsu, Takeshi Imamura
2018 Scientific Reports  
In this study, we addressed this issue by employing an approach based on texture analysis. Image texture analysis using the gray level co-occurrence matrix was explored to extract image features.  ...  X-rays and CT provide useful diagnostic information by detecting morphological changes in bone and calcified tissues, but these techniques are limited to detecting the late stages of OA progression.  ...  Acknowledgements The authors sincerely thank Drs. Yusuke Oshima, Sota Takanezawa and Ryosuke Kawakami of Ehime University for their helpful comments on this work.  ... 
doi:10.1038/s41598-018-21005-9 pmid:29434299 pmcid:PMC5809560 fatcat:3ygjba5ubzem5gtm2ierjh7pvi

Towards the improvement of textual anatomy image classification using image local features

Xiao Bing Huang, Tian Zhao, Yu Cao, Xiangming Mu, Pierre Tirilly
2011 Proceedings of the 2011 international ACM workshop on Medical multimedia analysis and retrieval - MMAR '11  
Last, a hybrid scheme on the results from the textual and visual methods is applied to achieved further improvement of the classification results.  ...  First, a mutual information (MI) based filter is applied to select a set of terms with top MI scores for each anatomical class and help reduce the noise existing in the raw text.  ...  Patch-based BoW models are used to classify endomicroscopic images [2] and breast tissue density in mammograms [4] . They are also effective in X-ray image classification [6, 3] .  ... 
doi:10.1145/2072545.2072551 fatcat:nhlmxwffijcqrp2jkjnn53shmm

The State of the Art of Medical Imaging Technology: from Creation to Archive and Back

Xiaohong W. Gao
2011 Open Medical Informatics Journal  
Stemming from the discovery of X-ray by Nobel laureate Wilhelm Roentgen, radiology was born, leading to the creation of large quantities of digital images as opposed to film-based medium.  ...  The focus of this paper is on content-based image retrieval (CBIR), in particular, for 3D images, which is exemplified by our developed online e-learning system, MIRAGE, home to a repository of medical  ...  ACKNOWLEDGEMENT The authors would like to acknowledge JISC ( at the UK for their continuously financial support for the two projects of MIRAGE and MIRAGE 2011, and thank European Commission  ... 
doi:10.2174/1874431101105010073 pmid:21915232 pmcid:PMC3170936 fatcat:jdbktuw4obg6jf35zrvoq47poq

A query expansion framework in image retrieval domain based on local and global analysis

M.M. Rahman, S.K. Antani, G.R. Thoma
2011 Information Processing & Management  
In this framework, images are represented by vectors of weighted concepts similar to the keyword-based representation used in text retrieval.  ...  We present an image retrieval framework based on automatic query expansion in a concept feature space by generalizing the vector space model of information retrieval.  ...  The authors would like to thank the CLEF organizers 3 for making the databases available for the experiments.  ... 
doi:10.1016/j.ipm.2010.12.001 pmid:21822350 pmcid:PMC3150552 fatcat:ow4wnbo7bfcvbd43svf7lh36c4

SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs

Jamil Ahmad, Muhammad Sajjad, Irfan Mehmood, Sung Wook Baik, Gayle E. Woloschak
2017 PLoS ONE  
The neural codes extracted from the entire image and salient part of the image are fused to obtain the saliency-injected neural codes (SiNC) descriptor which is used for indexing and retrieval.  ...  Comprehensive experimental evaluations on the radiology images dataset reveal that the proposed framework achieves high retrieval accuracy and efficiency for scalable image retrieval applications and compares  ...  The authors also thank the editor and anonymous reviewers for their prolific and highly constructive comments and suggestions which improved our manuscript significantly.  ... 
doi:10.1371/journal.pone.0181707 pmid:28771497 pmcid:PMC5542646 fatcat:vseqnumxhncafpz2gmpneb6opi

Combating Ambiguity for Hash-code Learning in Medical Instance Retrieval [article]

Jiansheng Fang, Huazhu Fu, Dan Zeng, Xiao Yan, Yuguang Yan, Jiang Liu
2021 arXiv   pre-print
The similarity between the query case and retrieved similar cases is determined by visual features extracted from pathologically abnormal regions.  ...  Extensive experiments on two medical image datasets demonstrate that Y-Net can alleviate the ambiguity of pathologically abnormal regions and its retrieval performance outperforms the state-of-the-art  ...  Recently, many existing works on instance-level retrieval typically extracted visual features by using convolutional neural networks (CNN) to prevent the visual features unique to an instance from drowning  ... 
arXiv:2105.08872v1 fatcat:5ga4eudoorchja5xwswm453jje

On the Automatic Generation of Medical Imaging Reports [article]

Baoyu Jing, Pengtao Xie, Eric Xing
2017 arXiv   pre-print
Medical imaging is widely used in clinical practice for diagnosis and treatment.  ...  We demonstrate the effectiveness of the proposed methods on two publicly available datasets.  ...  [16] adopt a CNN-RNN based framework to predict tags of chest x-ray images.  ... 
arXiv:1711.08195v2 fatcat:plcxiky6vndsli2mown7oqh3ee

Fine-grained histopathological image analysis via robust segmentation and large-scale retrieval

Xiaofan Zhang, Hai Su, Lin Yang, Shaoting Zhang
2015 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
We evaluate this proposed framework on a challenging and important clinical use case, i.e., differentiation of two types of lung cancers (the adenocarcinoma and the squamous carcinoma), using thousands  ...  ., cells) accurately, using hierarchical voting and repulsive active contour.  ...  It uses Gaussian mixture models (GMM) and informationtheoretic image matching via the Kullback-Leibler (K-L) measure to match and categorize X-ray images by body regions. Song et al.  ... 
doi:10.1109/cvpr.2015.7299174 dblp:conf/cvpr/ZhangSYZ15 fatcat:r3t6fuu4yvgphk4omnmvyxnzni
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