Conferences related to Colonography

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2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE


2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020)

The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2020 will be the 17th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2020 meeting will continue this tradition of fostering cross-fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging.ISBI 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2018 will be the 15th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2018 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2017 will be the 14th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2017 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI 2016)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forumfor the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2016 willbe the thirteenth meeting in this series. The previous meetings have played a leading role in facilitatinginteraction between researchers in medical and biological imaging. The 2016 meeting will continue thistradition of fostering crossfertilization among different imaging communities and contributing to an integrativeapproach to biomedical imaging across all scales of observation.

  • 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI 2015)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2015 will be the 12th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI 2014)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2014 will be the eleventh meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013)

    To serve the biological, biomedical, bioengineering, bioimaging and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2012 IEEE 9th International Symposium on Biomedical Imaging (ISBI 2012)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2011 IEEE 8th International Symposium on Biomedical Imaging (ISBI 2011)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2010 IEEE 7th International Symposium on Biomedical Imaging (ISBI 2010)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2009 IEEE 6th International Symposium on Biomedical Imaging (ISBI 2009)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2008 IEEE 5th International Symposium on Biomedical Imaging (ISBI 2008)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2007 IEEE 4th International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2007)

  • 2006 IEEE 3rd International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2006)

  • 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2004)

  • 2002 1st IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2002)


2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and severalco-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students, academics and industry researchers.

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conferenceand 27co-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students,academics and industry.

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    computer, vision, pattern, cvpr, machine, learning

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. Main conference plus 50 workshop only attendees and approximately 50 exhibitors and volunteers.

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Topics of interest include all aspects of computer vision and pattern recognition including motion and tracking,stereo, object recognition, object detection, color detection plus many more

  • 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Sensors Early and Biologically-Biologically-inspired Vision, Color and Texture, Segmentation and Grouping, Computational Photography and Video

  • 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics, motion analysis and physics-based vision.

  • 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics,motion analysis and physics-based vision.

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2005 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.


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Periodicals related to Colonography

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Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Computer Graphics and Applications, IEEE

IEEE Computer Graphics and Applications (CG&A) bridges the theory and practice of computer graphics. From specific algorithms to full system implementations, CG&A offers a strong combination of peer-reviewed feature articles and refereed departments, including news and product announcements. Special Applications sidebars relate research stories to commercial development. Cover stories focus on creative applications of the technology by an artist or ...


Image Processing, IEEE Transactions on

Signal-processing aspects of image processing, imaging systems, and image scanning, display, and printing. Includes theory, algorithms, and architectures for image coding, filtering, enhancement, restoration, segmentation, and motion estimation; image formation in tomography, radar, sonar, geophysics, astronomy, microscopy, and crystallography; image scanning, digital half-toning and display, andcolor reproduction.


Industrial Informatics, IEEE Transactions on

IEEE Transactions on Industrial Informatics focuses on knowledge-based factory automation as a means to enhance industrial fabrication and manufacturing processes. This embraces a collection of techniques that use information analysis, manipulation, and distribution to achieve higher efficiency, effectiveness, reliability, and/or security within the industrial environment. The scope of the Transaction includes reporting, defining, providing a forum for discourse, and informing ...


Information Technology in Biomedicine, IEEE Transactions on

Telemedicine, teleradiology, telepathology, telemonitoring, telediagnostics, 3D animations in health care, health information networks, clinical information systems, virtual reality applications in medicine, broadband technologies, and global information infrastructure design for health care.


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Most published Xplore authors for Colonography

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Xplore Articles related to Colonography

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Quantitative Analysis of Colonoscopy Skills Using the KAIST-Ewha Colonoscopy Simulator II

2007 Frontiers in the Convergence of Bioscience and Information Technologies, 2007

This paper presents a clinical evaluation of the KAIST-Ewha colonoscopy simulator II, which includes quantitative analysis of colonoscopy experts' and trainees' profiles during simulation. This version of the colonoscopy simulator employs an actual colonoscope with added electronics for simulation, and succeeds the previous version of the colonoscopy simulator with the specialized haptic device and proprietary colon modeler. Five colonoscopy experts ...


A gradient magnitude based region growing algorithm for accurate segmentation

Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101), 2000

An accurate segmentation is critical for clinical application of medical images. The undesirable partial-volume-effect, which lies on a boundary between a high intensity region and a low intensity region, makes unerring boundary determination a difficult task. A new approach to segmentation is required for removing the adverse effect on the boundary, which is unwanted especially from the point of view ...


Lines of Curvature for Polyp Detection in Virtual Colonoscopy

IEEE Transactions on Visualization and Computer Graphics, 2006

Computer-aided diagnosis (CAD) is a helpful addition to laborious visual inspection for preselection of suspected colonic polyps in virtual colonoscopy. Most of the previous work on automatic polyp detection makes use of indicators based on the scalar curvature of the colon wall and can result in many false-positive detections. Our work tries to reduce the number of false-positive detections in ...


Virtual dissection of the colon based on helical CT data-can it be done?

ISPA 2001. Proceedings of the 2nd International Symposium on Image and Signal Processing and Analysis. In conjunction with 23rd International Conference on Information Technology Interfaces (IEEE Cat., 2001

Colorectal cancer is the third most commonly diagnosed cancer; and colonic polyps are known precursors of that particular cancer. Virtual dissection refers to a display technique for polyp detection based on helical CT data, where the colon is dissected and flattened as on the pathologist's table. The approach and image processing as well as the early experience are described in ...


Content-based image retrieval on CT colonography using rotation and scale invariant features and bag-of-words model

2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010

We present a content-based image retrieval (CBIR) paradigm to enhance computed tomographic colonography computer-aided detection (CTCCAD). Our method uses scale-invariant feature transform (SIFT) features in conjunction with the bag- of-words model to describe and differentiate 3D images of CTCCAD detections. We evaluate the performance of our system using both digital colon phantoms and detections form CTCCAD. Our method shows promise ...


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Educational Resources on Colonography

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IEEE.tv Videos

No IEEE.tv Videos are currently tagged "Colonography"

IEEE-USA E-Books

  • Quantitative Analysis of Colonoscopy Skills Using the KAIST-Ewha Colonoscopy Simulator II

    This paper presents a clinical evaluation of the KAIST-Ewha colonoscopy simulator II, which includes quantitative analysis of colonoscopy experts' and trainees' profiles during simulation. This version of the colonoscopy simulator employs an actual colonoscope with added electronics for simulation, and succeeds the previous version of the colonoscopy simulator with the specialized haptic device and proprietary colon modeler. Five colonoscopy experts participated in the profiling of the experts' colonoscopy motions. Nine subjects consisting of three fellows and six residents participated in the training efficacy evaluation of the developed simulator. Two colon models constructed from patients' CT data are used for the training and the trainees' performance parameters are logged in real-time during simulation. Comparison of the trainees' profiles during the first 10 trials and the last 10 trials shows that the targeted colonoscopy skills are acquired well through the simulation-based training.

  • A gradient magnitude based region growing algorithm for accurate segmentation

    An accurate segmentation is critical for clinical application of medical images. The undesirable partial-volume-effect, which lies on a boundary between a high intensity region and a low intensity region, makes unerring boundary determination a difficult task. A new approach to segmentation is required for removing the adverse effect on the boundary, which is unwanted especially from the point of view of volume rendering. Here, the authors propose a gradient magnitude based region growing algorithm for accurate segmentation. The gradient is useful for enhancing the boundary because it emphasizes the difference among voxel values. By analyzing the gradient magnitude, the authors can see the sufficient contrast which must be presented on the boundary region and they use this contrast to increase the accuracy of their segmentation method. The authors pay attention only to the boundary region, not to the whole large volumetric dataset itself, making it more computationally efficient.

  • Lines of Curvature for Polyp Detection in Virtual Colonoscopy

    Computer-aided diagnosis (CAD) is a helpful addition to laborious visual inspection for preselection of suspected colonic polyps in virtual colonoscopy. Most of the previous work on automatic polyp detection makes use of indicators based on the scalar curvature of the colon wall and can result in many false-positive detections. Our work tries to reduce the number of false-positive detections in the preselection of polyp candidates. Polyp surface shape can be characterized and visualized using lines of curvature. In this paper, we describe techniques for generating and rendering lines of curvature on surfaces and we show that these lines can be used as part of a polyp detection approach. We have adapted existing approaches on explicit triangular surface meshes, and developed a new algorithm on implicit surfaces embedded in 3D volume data. The visualization of shaded colonic surfaces can be enhanced by rendering the derived lines of curvature on these surfaces. Features strongly correlated with true-positive detections were calculated on lines of curvature and used for the polyp candidate selection. We studied the performance of these features on 5 data sets that included 331 pre-detected candidates, of which 50 sites were true polyps. The winding angle had a significant discriminating power for true-positive detections, which was demonstrated by a Wilcoxon rank sum test with p<0.001. The median winding angle and inter-quartile range (IQR) for true polyps were 7.817 and 6.770-9.288 compared to 2.954 and 1.995-3.749 for false-positive detections

  • Virtual dissection of the colon based on helical CT data-can it be done?

    Colorectal cancer is the third most commonly diagnosed cancer; and colonic polyps are known precursors of that particular cancer. Virtual dissection refers to a display technique for polyp detection based on helical CT data, where the colon is dissected and flattened as on the pathologist's table. The approach and image processing as well as the early experience are described in this paper.

  • Content-based image retrieval on CT colonography using rotation and scale invariant features and bag-of-words model

    We present a content-based image retrieval (CBIR) paradigm to enhance computed tomographic colonography computer-aided detection (CTCCAD). Our method uses scale-invariant feature transform (SIFT) features in conjunction with the bag- of-words model to describe and differentiate 3D images of CTCCAD detections. We evaluate the performance of our system using both digital colon phantoms and detections form CTCCAD. Our method shows promise in distinguishing common structures found within the colon.

  • Accurate and fast 3D colon segmentation in CT colonography

    This paper introduces an adaptive level set method for 3D segmentation of colon tissue in CT colonography filled with air and opacified fluid. First, most of the opacified liquid is removed by a threshold value. The closed contours are propagated toward the desired 3D region boundaries through the iterative evolution of the adaptive level sets function. The proposed method has been tested on 22 real CT colonography datasets with various pathologies, and the segmentation accuracy has achieved 98.40%.

  • Automatic correction of level set based subvoxel accurate centerlines for virtual colonoscopy

    Virtual colonoscopy (VC) is becoming a more prevalent way to diagnose colon cancer. One of the critical elements in detecting cancerous polyps using VC in conjunction with computer-aided detection is that the colon centerline be determined accurately. The amount of colonic distention can vary from patient to patient, which may cause loops and multiple disconnected segments to appear in the colon segmentation. These variations have caused previous centerline algorithms to fail to capture a complete and accurate centerline for all colons. We have developed an automatic method to determine from a CT VC scan a subvoxel accurate centerline, which is accurate even in cases of over- or underdistended colons. We have demonstrated successfully the effectiveness of our algorithm on 50 cases, half of which resulted in erroneous solutions by previous centerline algorithms

  • CURRENT CONCEPTS IN COMPUTER-AIDED DETECTION FOR CT COLONOGRAPHY

    Computer-aided detection (CAD) for CT colonography has been under development for about eight years. It is now sufficiently accurate that clinically significant polyps 1 cm and larger can be reliably detected with 90% sensitivity. The research focus is now shifting to improving sensitivity for detection of smaller polyps, reducing the number of false positive detections, integrating CAD into clinical practice and applying CAD to the setting of fecal tagging and laxative-free bowel preparations. This is a dynamic research field which requires the use of state-of-the-art image processing and machine learning techniques

  • Matching colonic polyps from prone and supine CT colonography scans based on statistical curvature information

    Computed tomographic colonography (CTC) provides a feasible way for the detection of colorectal polyps and cancer screening. In the clinical practice of CTC, a true colonic polyp will be confirmed with high confidence if a radiologist can find it in both the supine and prone scans. To assist radiologists in CTC reading, we propose a new colonic polyp matching method based on statistical curvature information of polyp candidates. We first extract histograms of curvature-related features (HCF) from each polyp candidate, then use diffusion map to embed the original high dimensional data into a low-dimensional space. Experimental results show that by using our HCF method, we can improve the sensitivity from 0.58 to 0.74 at false positive rate 0.1 compared with a traditional method that uses only means of curvature- related features.

  • Massive-training artificial neural networks for CAD for detection of polyps in CT colonography: False-negative cases in a large multicenter clinical trial

    A major challenge in computer-aided detection (CAD) of polyps in CT colonography (CTC) is the detection of "difficult" polyps which radiologists are likely to miss. Our purpose was to develop massive-training artificial neural networks (MTANNs) for improving the performance of a CAD scheme on false-negative cases in a large multicenter clinical trial. We developed 3D MTANNs designed to differentiate between polyps and several types of non- polyps and tested on 14 polyps/masses that were actually "missed" by radiologists in the trial. Our initial CAD scheme detected 71.4% of "missed" polyps with 18.9 false positives (FPs) per case. The MTANNs removed 75% of the FPs without loss of any true positives; thus, the performance of our CAD scheme was improved to 4.8 FPs per case at the sensitivity of 71.4% of the polyps "missed" by radiologists.



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