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Image Retrieval Method for Multiscale Objects from Optical Colonoscopy Images

Hirokazu Nosato, Hidenori Sakanashi, Eiichi Takahashi, Masahiro Murakawa, Hiroshi Aoki, Ken Takeuchi, Yasuo Suzuki
2017 International Journal of Biomedical Imaging  
In order to assist diagnoses with optical colonoscopy, this paper proposes a retrieval method for colonoscopy images that can cope with multiscale objects.  ...  The proposed method can retrieve similar colonoscopy images despite varying visible sizes of the target objects.  ...  Conclusion This study has proposed a method of retrieving multiscale objects from optical colonoscopy images based on HLAC.  ... 
doi:10.1155/2017/7089213 pmid:28255295 pmcid:PMC5309433 fatcat:tnlx4hlt3jf2hojudtkpmnigv4

2011 Index IEEE Transactions on Information Technology in Biomedicine Vol. 15

2011 IEEE Transactions on Information Technology in Biomedicine  
Verhaert, V., +, TITB Sept. 2011 787-794 Biomedical image processing Optimized Weighted Performance Index for Objective Evaluation of Border- Detection Methods in Dermoscopy Images.  ...  Zhang, Z-.Q., +, TITB July 2011 513-521 Border detection Optimized Weighted Performance Index for Objective Evaluation of Border- Detection Methods in Dermoscopy Images.  ... 
doi:10.1109/titb.2011.2177396 fatcat:kqz7azo7tfcwxjw3jxvbvb3qom

Medical Video Super-Resolution Based on Asymmetric Back-Projection Network with Multilevel Error Feedback

Sheng Ren, Jianqi Li, Kehua Guo, Fangfang Li
2021 IEEE Access  
Medical video is important for medical diagnosis.  ...  We construct a single-frame medical video super-resolution model as the benchmark model, combine the optical flow algorithm and multiframe fusion strategy to propose a medical video super-resolution method  ...  This article is extended from the Conference paper written by Sheng Ren in The 12th IEEE International Conference on Cyber, Physical and Social Computing (Towards Efficient Medical Video Super-Resolution  ... 
doi:10.1109/access.2021.3054433 fatcat:fyju5efvdbe5fd4q35i7m3d7vq

Content-based processing and analysis of endoscopic images and videos: A survey

Bernd Münzer, Klaus Schoeffmann, Laszlo Böszörmenyi
2017 Multimedia tools and applications  
Many post-processing problems are based on typical Multimedia methods like indexing, retrieval, summarization and video interaction, but have only been sparsely addressed so far for this domain.  ...  Proposed works mainly include image processing techniques, pattern recognition, machine learning methods and Computer Vision algorithms.  ...  image retrieval (CBIR).  ... 
doi:10.1007/s11042-016-4219-z fatcat:zuqeagbwzrhpfeuk7k2ucay66e

A standardised protocol for texture feature analysis of endoscopic images in gynaecological cancer

Marios S Neofytou, Vasilis Tanos, Marios S Pattichis, Constantinos S Pattichis, Efthyvoulos C Kyriacou, Dimitris D Koutsouris
2007 BioMedical Engineering OnLine  
For endoscopic imaging of the endometrium, we propose a standardized image acquisition protocol to eliminate significant statistical differences due to variations in: (i) the distance from the tissue (  ...  Yet, significant differences can arise due to variations in the image acquisition method.  ...  Figure 4 illustrates the original chicken cavity images for panoramic and close up views (ROI images after multiscale analysis for the scales 2x2 to 5x5).  ... 
doi:10.1186/1475-925x-6-44 pmid:18047655 pmcid:PMC2246140 fatcat:76hq7rscqvhlbi2i3rymszk6ci

Front Matter: Volume 10134

2017 Medical Imaging 2017: Computer-Aided Diagnosis  
Publication of record for individual papers is online in the SPIE Digital Library. Paper Numbering: Proceedings of SPIE follow an e-First publication model.  ...  to optic pathway glioma segmentation [10134-58] BRAIN 10134 1P Deep learning for segmentation of brain tumors: Can we train with images from different institutions?  ...  A novel 3D shape descriptor for automatic retrieval of anatomical structures from medical images [10134-106] 10134 31 Application of convolutional artificial neural networks to echocardiograms for  ... 
doi:10.1117/12.2277119 dblp:conf/micad/X17 fatcat:ika7pheqxngdxejyvkss4dkbv4

A Supervised Learning Approach for Crohn's Disease Detection Using Higher-Order Image Statistics and a Novel Shape Asymmetry Measure

Dwarikanath Mahapatra, Peter Schueffler, Jeroen A. W. Tielbeek, Joachim M. Buhmann, Franciscus M. Vos
2013 Journal of digital imaging  
The current reference standard for diagnosis, colonoscopy, is time-consuming and invasive while magnetic resonance imaging (MRI) has emerged as the preferred noninvasive procedure over colonoscopy.  ...  We propose a supervised learning method for the identification and localization of regions in abdominal magnetic resonance images that have been affected by CD.  ...  [9] addressed the tasks of localization, annotation, or classification of optical biopsies in colonoscopy.  ... 
doi:10.1007/s10278-013-9576-9 pmid:23392736 pmcid:PMC3782610 fatcat:gtztzqw4lbd2bbleujwheiqeci

Applications of Artificial Intelligence for the Diagnosis of Gastrointestinal Diseases

Silvia Pecere, Sebastian Manuel Milluzzo, Gianluca Esposito, Emanuele Dilaghi, Andrea Telese, Leonardo Henry Eusebi
2021 Diagnostics  
AI networks have been trained to differentiate benign from malignant lesions, analyze endoscopic and radiological GI images, and assess histological diagnoses, obtaining excellent results and high overall  ...  for future development.  ...  Preoperative arterial and portal phase contrast-enhanced CT images were retrieved.  ... 
doi:10.3390/diagnostics11091575 pmid:34573917 fatcat:kd4fku43lbgkbiwldmy5nytcta

Front Matter: Volume 7260

Proceedings of SPIE, Nico Karssemeijer, Maryellen L. Giger
2009 Medical Imaging 2009: Computer-Aided Diagnosis  
Utrecht (Netherlands) 7260 1J Automated detection of kinks from blood vessels for optic cup segmentation in retinal images [7260-54] D. W. K. Wong, J. Liu, J. H. Lim, H.  ...  Bergen, Fraunhofer-Institut für Integrierte Schaltungen (Germany) 7260 26 A fully automatic lesion detection method for DCE-MRI fat-suppressed breast images [7260-76] A. x Downloaded From:  ...  methods for evaluation of imaging systems.  ... 
doi:10.1117/12.829302 dblp:conf/micad/X09 fatcat:jgk7ro3fazeuhl7j7zo3y57aki

A survey on deep learning in medical image analysis

Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen A.W.M. van der Laak, Bram van Ginneken, Clara I. Sánchez
2017 Medical Image Analysis  
We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks and provide concise overviews of studies per application area.  ...  Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images.  ...  ArXiv was searched for papers mentioning one of a set of terms related to medical imaging.  ... 
doi:10.1016/ pmid:28778026 fatcat:esbj72ftwvbgzh6jgw367k73j4

Graphics, Vision, and Visualization in Medical Imaging: A State of the Art Report [article]

Norberto Ezquerra, Isabel Navazo, Tahia Infantes Morris, Eva Monclus
1999 Eurographics State of the Art Reports  
The overall objective is therefore to provide a "snap shot" of the field through a brief summary that will hopefully serve as a useful source of information for those wanting to learn more about the field  ...  As the title of this paper suggests, one interesting result of this evolutionary process has been the fusion of traditionally disjointed yet highly interrelated areas: from computer vision and image processing  ...  A related concept is that of retrieving images, which may also prove useful for indexing into large image DBs [Dec95] . EUROGRAPHICS'99 / B. Falcidieno, J. Rossignac.  ... 
doi:10.2312/egst.19991067 fatcat:xb3sv64whrh4vj22a6caleffby

Local fractal dimension based approaches for colonic polyp classification

Michael Häfner, Toru Tamaki, Shinji Tanaka, Andreas Uhl, Georg Wimmer, Shigeto Yoshida
2015 Medical Image Analysis  
With this database, the viewpoint invariance of the methods is assessed, an important features for the employed endoscopic image databases.  ...  The three proposed extensions are the best performing methods or at least among the best performing methods for each of the employed databases.  ...  Scale and viewpoint invariance is essential for good retrieval results in case of the UIUCtex database, since the distances from the query image to the other images from the same class as the query image  ... 
doi:10.1016/ pmid:26385078 fatcat:wboxua6cnbcfli3vd7mpoetxbe

Machine learning and radiology

Shijun Wang, Ronald M. Summers
2012 Medical Image Analysis  
diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding  ...  Technology development in machine learning and radiology will benefit from each other in the long run.  ...  Acknowledgments We thank Andrew Dwyer, MD, for critical review of the manuscript. This manuscript was support by the Intramural Research Program of the National Institutes of Health Clinical Center.  ... 
doi:10.1016/ pmid:22465077 pmcid:PMC3372692 fatcat:4ynexgzdhrev7dfqapmjpxexuu

Deep Learning in Head and Neck Tumor Multiomics Diagnosis and Analysis: Review of the Literature

Xi Wang, Bin-bin Li
2021 Frontiers in Genetics  
Among the DL techniques, the convolution neural network (CNN) is used for image segmentation, detection, and classification and in computer-aided diagnosis.  ...  Deep learning (DL), a type of artificial intelligence (AI), is applied in medical image analysis.  ...  A new loss function, class-wise DSC loss, for training the segmentation network of colonoscopy pathology images was presented by Feng et al. (2020) .  ... 
doi:10.3389/fgene.2021.624820 pmid:33643386 pmcid:PMC7902873 fatcat:eofflp46c5h6pd5gbni7sdnp5u

Artificial Intelligence in Translational Medicine

Simone Brogi, Vincenzo Calderone
2021 International Journal of Translational Medicine  
in breakthroughs for advancing human health.  ...  Consequently, during the last decade the system for managing, analyzing, processing and extrapolating information from scientific data has been considerably modified in several fields, including the medical  ...  They proposed a multimodal and multiscale ML-based method in which information from magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) images were combined within  ... 
doi:10.3390/ijtm1030016 fatcat:c6g6ld26gjg6jbkcddauo44qvu
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