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IEEE Ro-Man DABI 2018 : The Development and Application of Advanced Bio-medical Imaging based on the Computer Vision

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Link: http://ro-man2018.org/special-session-6-computer-vision-and-machine-learning-foundations-and-applications-in-advanced-bio-medical-applications/
 
When Aug 27, 2018 - Aug 31, 2018
Where Nanjing/Tai'an
Abstract Registration Due May 1, 2018
Submission Deadline Jun 1, 2018
Notification Due Jul 1, 2018
Final Version Due Aug 1, 2018
 

Call For Papers

Organisers: Shuihua Wang, Liangxiu Han, Zhengchao Dong (China)

Contact: shuihuawang@ieee.org

(The code for the submission: 4a64a)



With advancement in bio-medical imaging, the amount of data generated by multimodality image techniques (e.g. ranging from Computed Tomography (CT), Magnetic Resonance Imaging (MR), Ultrasound, Single Photon Emission Computed Tomography (SPECT), and Positron Emission Tomography (PET), to Magnetic Particle Imaging, EE/MEG, Optical Microscopy and Tomography, Photoacoustic Tomography, Electron Tomography, and Atomic Force Microscopy, etc.) has grown exponentially and the nature of such data is increasingly become more complex. This poses a great challenge on how to develop new advanced imaging methods and computational models based in the computer vision for efficient data processing, analysis and modelling in clinical applications and in understanding the underlying biological process.

The purpose of this workshop is to provide a diverse, but complementary, set of contributions to demonstrate new developments and applications of advanced imaging analysis in the multimodel biomedical imaging area. The ultimate goal is to promote research and development of advanced imaging analysis for multimodal biomedical images by publishing high-quality research articles and reviews in this rapidly growing interdisciplinary field.

List of topics

The topics of interest include, but are not limited to:
- New algorithms, models and applications of advanced imaging methods
- Multimodal imaging techniques: data acquisition, reconstruction; 2D, 3D, 4D imaging, etc.)
- Translational multimodality imaging and biomedical applications (e.g., detection, diagnostic analysis, quantitative measurements, image guidance of ultrasonography)
- Variational and combinatorial optimizations for biomedical imaging and image analysis
- Advanced Biomedical image analysis (image processing, Statistical and probabilistic methods for biomedical imaging and image analysis, Machine learning in biomedical imaging and image analysis)
- Visualization

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