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IPL at ImageCLEF 2017 Concept Detection Task

Leonidas Valavanis, Spyridon Stathopoulos
2017 Conference and Labs of the Evaluation Forum  
The visual representation of images was based on the well known, bag of visual words and bag-of-colors models.  ...  A probabilistic k-nearest neighbor approach was used for automatically detecting multiple concepts in medical images.  ...  The BoC model was used for classification of biomedical images in [4] and it was shown that it is combined successfully with the BoW-SIFT model in a late fusion manner.  ... 
dblp:conf/clef/ValavanisS17 fatcat:w2zflzdi5vfkbjwjqs5zqdh7uu

IBM T.J. Watson Research Center, Multimedia Analytics: Modality Classification and Case-Based Retrieval Tasks of ImageCLEF2012

Liangliang Cao, Yuan-Chi Chang, Noel C. F. Codella, Michele Merler, Quoc-Bao Nguyen, John R. Smith
2012 Conference and Labs of the Evaluation Forum  
In this paper we present the modeling strategies that were applied by the IBM T.J. Watson research team to the modality classification and case-based retrieval tasks of ImageCLEF 2012.  ...  For the case based retrieval task, we employed a semantic similarity approach to measure the relatedness among medical concepts found in the text corpus.  ...  In the biomedical domain, the terminology is very important because the words used in the document are related to medical terms that can refer to the same concept with different semantic interpretation  ... 
dblp:conf/clef/CaoCCMNS12 fatcat:teigaj4bmbe23j2yqf5am62fhi

Chest pathology detection using deep learning with non-medical training

Yaniv Bar, Idit Diamant, Lior Wolf, Sivan Lieberman, Eli Konen, Hayit Greenspan
2015 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)  
In this work, we examine the strength of deep learning approaches for pathology detection in chest radiographs.  ...  We explore the ability of CNN learned from a non-medical dataset to identify different types of pathologies in chest x-rays. We tested our algorithm on a 433 image dataset.  ...  We thank our colleagues from the Diagnostic Imaging Department of Sheba Medical Center, Tel Hashomer, Israel -for the data collection used in this work.  ... 
doi:10.1109/isbi.2015.7163871 dblp:conf/isbi/BarDWLKG15 fatcat:am3kut7x5vhjpfoqte6uow2hnu

Medical image retrieval using bag of meaningful visual words

Antonio Foncubierta-Rodríguez, Alba García Seco de Herrera, Henning Müller
2013 Proceedings of the 1st ACM international workshop on Multimedia indexing and information retrieval for healthcare - MIIRH '13  
The bag-of-visual-words approach is a widely used technique that tries to shorten the semantic gap by learning meaningful features from the dataset and describing documents and images in terms of the histogram  ...  In this work a visual vocabulary pruning technique is presented. It enormously reduces the amount of required words to describe a medical image dataset with no significant effect on the accuracy.  ...  This work was partially supported by the Swiss National Science Foundation (FNS) in the MANY2 project (205320-141300), the EU 7 th Framework Program under grant agreements 257528 (KHRESMOI) and 258191  ... 
doi:10.1145/2505323.2505336 dblp:conf/mm/RodriguezHM13 fatcat:akns54zeuvbi7k6bvbbv2nrukm

Hierarchical medical image annotation using SVM-based approaches

Igor F. Amaral, Filipe Coelho, Joaquim F. Pinto da Costa, Jaime S. Cardoso
2010 Proceedings of the 10th IEEE International Conference on Information Technology and Applications in Biomedicine  
Support Vector Machines (SVMs): first we concatenate global image descriptors with an interest points Bag-of-Words (BoW) to build a feature vector; second, we perform an initial annotation of the data  ...  In this work we address the problem of hierarchical medical image annotation by building a Content Based Image Retrieval (CBIR) system aiming to explore the combination of three different methods using  ...  This year, dense sampled local descriptors in a Bag-of-Words (BoW) with SVMs for annotation attained the best results.  ... 
doi:10.1109/itab.2010.5687655 fatcat:2dfyigg2yjarznu6nzlhdfbidy

Retrieval of high-dimensional visual data: current state, trends and challenges ahead

Antonio Foncubierta-Rodríguez, Henning Müller, Adrien Depeursinge
2013 Multimedia tools and applications  
quickly increasing quantities, for example in medical tomographic imaging.  ...  First, free text information of documents from varying sources became accessible in addition to structured data in databases, initially for exact search and then for more probabilistic models.  ...  Bag-of-words or bag-of-visualwords attempt to learn concepts from the features, clustering the feature space into densely populated regions that might represent visual concepts in the images.  ... 
doi:10.1007/s11042-012-1327-2 fatcat:nmhj5uwedbcedpzelg2ptqkqce

IPL at ImageCLEF 2018: A kNN-based Concept Detection Approach

Leonidas Valavanis, Theodore Kalamboukis
2018 Conference and Labs of the Evaluation Forum  
The visual representation of images was based on the bagof-visual-words and bag-of-colors models. Our proposed algorithm was ranked 13th among 28 runs and our top run achieved F1 score 0.0509.  ...  In this paper we present the methods and techniques performed by the IPL Group for the Concept Detection subtask of the Im-ageCLEF 2018 Caption Task.  ...  Bag-of-visual Words (BoVW) The BoVW model has shown promising results in the field of classification and image retrieval.  ... 
dblp:conf/clef/ValavanisK18 fatcat:t2ak3y2plvhgjiivgcto2a7sbm

Multimodal page classification in administrative document image streams

Marçal Rusiñol, Volkmar Frinken, Dimosthenis Karatzas, Andrew D. Bagdanov, Josep Lladós
2014 International Journal on Document Analysis and Recognition  
A final step uses an n-gram model of the page stream allowing a finergrained classification of pages.  ...  In this paper we present a page classification application in a banking workflow. The proposed architecture represents administrative document images by merging visual and textual descriptions.  ...  Refinements of the bag-of-words model for both feature selection (e.g.  ... 
doi:10.1007/s10032-014-0225-8 fatcat:lqln4dntabefpa65qcjd6nrxl4

Traditional Feature Engineering and Deep Learning Approaches at Medical Classification Task of ImageCLEF 2016

Sven Koitka, Christoph M. Friedrich
2016 Conference and Labs of the Evaluation Forum  
In addition Bag-of-Visual-Words (BoVW) were computed in Opponent color space, since some classes in this subtask can be distinguished by color.  ...  This paper describes the modeling approaches used for the Subfigure Classification subtask at ImageCLEF 2016 by the FHDO Biomedical Computer Science Group (BCSG).  ...  Conclusions Several approaches for modality classification of medical images were evaluated for the ImageCLEF 2016 medical task.  ... 
dblp:conf/clef/KoitkaF16 fatcat:3kqxj5tsrnadxckra3bqb6k2ja

Bag of Visual Words Techniques for Content- Based Image Retrieval and the Role Using in Computer Vision Major: A Survey

Abdullah MMA Al-Omari, Abdullah Noman
2021 Zenodo  
Further, CBIR became the main direction for image retrieval, likewise the bag-of-visual- word model (BoVW), which is a popular helpful model for achieving CBIR goals.  ...  Although, other specific methods are used either for medical images or for streaming images. In this work, various methods of different types have been presented.  ...  Acknowledgment I thank Almighty Allah for instructing, teaching, and leading me throughout us life and specifically in this research work.  ... 
doi:10.5281/zenodo.5448762 fatcat:go4qzq6ktrcp5d6nvs7royxokm

Automated Recognition of Alzheimer's Dementia using Bag-of-Deep-Features and Model Ensembling

Zafi Sherhan Syed, Muhammad Shehram Shah Syed, Margaret Lech, Elena Pirogova
2021 IEEE Access  
The bag-of-words (BoW) method is a popular approach for generating word-frequency based representation of text documents in the field of natural language processing.  ...  [71] , [72] as an improvement to the bag-of-visual-words method for computer vision applications.  ... 
doi:10.1109/access.2021.3090321 fatcat:gtdhwkxjb5ci7e4lvndkbj6ue4

A Modified HSIFT Descriptor for Medical Image Classification of Anatomy Objects

Sumeer Ahmad Khan, Yonis Gulzar, Sherzod Turaev, Young Suet Peng
2021 Symmetry  
Modeling low level features to high level semantics in medical imaging is an important aspect in filtering anatomy objects.  ...  Bag of Visual Words (BOVW) representations have been proven effective to model these low level features to mid level representations.  ...  Acknowledgments: The authors would like to thank the United Arab Emirates University for funding this work under Start-Up grant G00003321.  ... 
doi:10.3390/sym13111987 doaj:4655ef7b4db9439bb9576e0dd8a3085d fatcat:3qide2brpndghee5g64yii4wru

Reducing Annotation Burden Through Multimodal Learning

Kevin Lopez, Samah J. Fodeh, Ahmed Allam, Cynthia A. Brandt, Michael Krauthammer
2020 Frontiers in Big Data  
In this study, we examined deep learning-based multimodal fusion techniques for the combined classification of radiological images and associated text reports.  ...  Overall, our results suggest the potential of multimodal learning to decrease the need for labeled training data resulting in a lower annotation burden for domain experts.  ...  ACKNOWLEDGMENTS We would also like to thank Mate Nagy for his early insights and input on developing the model architecture.  ... 
doi:10.3389/fdata.2020.00019 pmid:33693393 pmcid:PMC7931886 fatcat:kwhnbpe3qrdb3bikl4cneucwla

Visual Character N-Grams for Classification and Retrieval of Radiological Images

Pradnya Kulkarni, Andrew Stranieri, Siddhivinayak Kulkarni, Julien Ugon, Manish Mittal
2014 The International Journal of Multimedia & Its Applications  
We propose the use of visual character n-gram model for representation of image for classification and retrieval purposes.  ...  Character n-gram model has been effective in text retrieval context in languages such as Chinese where there are no clear word boundaries.  ...  A bag of words model used effectively in text retrieval is further extended as Bag-of-visual-words for image classification and retrieval [33] [39] .  ... 
doi:10.5121/ijma.2014.6204 fatcat:avwsnclfpzd5ldyiihufrjwwvu

Classification of Alzheimer's disease subjects from MRI using hippocampal visual features

Olfa Ben Ahmed, Jenny Benois-Pineau, Michèle Allard, Chokri Ben Amar, Gwénaëlle Catheline
2014 Multimedia tools and applications  
Indexing and classification tools for Content Based Visual Information Retrieval (CBVIR) have been penetrating the universe of medical image analysis.  ...  In this paper, we develop an automatic classification framework for AD recognition in structural Magnetic Resonance Images (MRI).  ...  Some works [14] [29] on MRI classification for AD diagnosis evaluate the suitability of the Bag-of-Visual-Words (BoVW) approach for automatic classification of MR images in the case of Alzheimer's disease  ... 
doi:10.1007/s11042-014-2123-y fatcat:sxc25jbffbbfvifxwlva3tw2r4
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