Advanced Signal Processing in Biomedical Imaging

  in Special Issue   Posted on August 13, 2017

Information for the Special Issue

Special Issue Call for Papers:

Overview:

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

The purpose of this special issue is to provide a diverse, but complementary, set of contributions to demonstrate new developments and applications of advanced imaging analysis in the multimodal 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.

Topics:

The topics of interest include:

  • 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)
  • Deep learning methods (convolutional neural network, autoencoder, deep belief network, etc.)
  • Visualization

Submission Guidelines:

Research articles must not have been published or submitted for publication elsewhere. All articles will be peer reviewed and accepted based on quality, originality, novelty, and relevance to the special issue theme. Before submission authors should carefully read over the journal\’s Author Guidelines, which is available at http://www.elsevier.com/wps/find/journaldescription.cws_home/367/authorinstructions. Manuscripts must be submitted online at: https://www.evise.com/profile/#/COMPELECENG/login using Article Type SI-spbio under the \”Issues\” tab.

Schedule:

Submission of Manuscript: November 1, 2017

First notification: Jan. 1, 2018

Submission of revised manuscript: March 1, 2018

Notification of the re-review: April 1, 2018

Final Notification: June 1, 2018

Final paper due: July 1, 2018

Publication date: November 2018

Guest Editors:

Yudong Zhang, PhD (Managing Guest Editor)
NanjingNormalUniversity
Nanjing, China
yudongzhang@ieee.org, zhangyudong@njnu.edu.cn

Liangxiu Han, PhD
ManchesterMetropolitanUniversity
Manchester, UK
l.han@mmu.ac.uk

Zhengchao Dong, PhD
ColumbiaUniversity
New York, USA
zd2109@cumc.columbia.edu

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