Development of new convolutional neural networks architectures in Medical Imaging

  in Special Issue   Posted on September 28, 2020

Information for the Special Issue

Submission Deadline: Wed 30 Sep 2020
Journal Impact Factor : 3.750
Journal Name : Computerized Medical Imaging and Graphics
Journal Publisher:
Website for the Special Issue:
Journal & Submission Website:

Special Issue Call for Papers:

I. Special issue title: Special Issue on Development of new convolutional neural networks architectures in Medical Imaging

II. Aim and Scope:

Nowadays, methods of convolutional neural network (CNN) play an important role in medical imaging research, which brings together complementary interdisciplinary research practice, in the development of innovative computer-aided diagnosis (CAD) system, medical imaging reconstruction and segmentation, etc. In the last five years, the successful development of various CNN architectures has significantly improved the performance in medical imaging in terms of diagnostic efficiency, imaging quality, and disease classification accuracy.

Recent research indicates that the different architectures of CNN can help achieve an outstanding performance for particular types of medical imaging applications. With the rapidly growing complexities of design issues, methodologies and more demanding quality of medical imaging applications, the development of novel CNN architectures for medical imaging becomes timely and of high relevance. This special issue intends to bring together researchers to report the recent findings in new convolutional neural networks architectures for Medical Imaging.

III. Topics of interest

This special issue seeks to present and highlight the state-of-the art CNN architectures in medical imaging.

Topics include but are not limited to:

  • Computer-aided diagnosis in medical imaging including CT, ultrasound, optical, MRI, and EIT
  • Segmentation in medical imaging
  • Nosie removal in medical imaging
  • Disease classification in medical imaging
  • Medical Image reconstruction

IV. Important Date

  • Manuscript submission open: 01 Mar 2020
  • Manuscript submission deadline: 30 Sep 2020
  • Review notification: 30 Nov 2020
  • Revised version submission: 30 Jan 2020
  • Final notification: 15 Mar 2021


Papers will be evaluated based on their originality, presentation quality, and relevance to the theme of the special issue. The submitted papers must be clearly written in excellent English and must present original research that has not been published nor currently under review elsewhere. A successful theoretical paper would present significant contributions to the areas of convolutional neural networks. A successful application-driven paper should employ artificial intelligence to high impact medical imaging applications and extensive experimentation supporting the results. Manuscripts based on conference papers must contain a substantial amount of essentially new material, preferably to the extent of a new paper. The conference publication(s) must be cited in the manuscript and the new contributions must be clearly stated. Submissions must conform to the layout, format and page limit provided in the guidelines for authors.

VI. Guest Editors

1. Name: Steve S. H. Ling

Brief biography: S.H. Ling received the Ph.D. degree from the Department of Electronic and Information Engineering in the Hong Kong Polytechnic University in 2006. Currently, he works in University of Technology, Sydney, Australia as Senior Lecturer. His current research interests include deep learning and medical imaging. He has authored and coauthored over 170 books, book chapters, journal and conference papers on computational intelligence and its industrial applications. Currently, he serves as Editor-in-Chief for Journal of Intelligent Learning Systems and Applications and Associate Editor for Electronic Letters. In 2012 and 2014, he had been lead guest editor on International Journal of Bioinformatics Research and Applications and Applied Soft Computing. He is a Senior member of IEEE.

2. Name: H.K. Lam

H. K. Lam received the B.Eng. (Hons.) and Ph.D. degrees from the Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, in 1995 and 2000, respectively. During the period of 2000 and 2005, he worked with the Department of Electronic and Information Engineering at The Hong Kong Polytechnic University as Post-Doctoral Fellow and Research Fellow respectively. He joined as a Lecturer at King’s College London in 2005 and is currently a Reader.

His current research interests include intelligent control, computational intelligence and machine learning. He has authored/co-authored over 330 publications (3 monographs, 2 edited book, 8 editorials, 6 book chapters, 195 journal papers and 120 conference papers). He has served as a program committee member, international advisory board member, invited session chair and publication chair for various international conferences and a reviewer for various books, international journals and international conferences. He was an associate editor for IEEE Transactions on Fuzzy Systems (2009-2018). He is an associate editor IEEE Transactions on Circuits and Systems II: Express Briefs, IET Control Theory and Applications, International Journal of Fuzzy Systems and Neorocomputing; and guest editor for many international journals. He is in the editorial board of Journal of Intelligent Learning Systems and Applications, Journal of Applied Mathematics, Mathematical Problems in Engineering, Machines, Modelling and Simulation in Engineering, Annual Review of Chaos Theory, Bifurcations and Dynamical System, The Open Cybernetics and Systemics Journal, Cogent Engineering and International Journal of Sensors, Wireless Communications and Control. He is an IEEE senior member.

He is a coeditor of two edited volumes: Control of Chaotic Nonlinear Circuits (World Scientific, 2009) and Computational Intelligence and Its Applications (World Scientific, 2012), and author/coauthor of three monographs: Stability Analysis of Fuzzy-Model-Based Control Systems (Springer, 2011), Polynomial Fuzzy Model Based Control Systems (Springer, 2016) and Analysis and Synthesis for Interval Type-2 Fuzzy-Model-Based Systems (Springer, 2016).

He is named in the 2018 Clarivate Analytics Highly Cited Researchers List.

Further details can be found in

3. Name: K.M. Lam

Kin-Man Lam received his Associateship in Electronic Engineering with distinction from the Hong Kong Polytechnic in 1986. He was awarded an M.Sc. degree in communication engineering from the Department of Electrical Engineering, Imperial College of Science, Technology and Medicine, England, in 1987, and a Ph.D. degree from the Department of Electrical Engineering at the University of Sydney, Australia in 1996.

He joined the Department of Electronic and Information Engineering, The Hong Kong Polytechnic University again as an Assistant Professor in October 1996. He became an Associate Professor in 1999, and has been a Professor since 2010. He was actively involved in professional activities. He has been a member of the organizing committee or program committee of many international conferences. In particular, he was the Secretary of the 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP’03), the Technical Chair of the 2004 International Symposium on Intelligent Multimedia, Video and Speech Processing (ISIMP 2004), a Technical Co-Chair of the 2005 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS 2005), a secretary of the 2010 International Conference on Image Processing (ICIP 2010), a Technical Co-Chair of 2010 Pacific-Rim Conference on Multimedia (PCM 2010), and a General Co-Chair of the 2012 IEEE International Conference on Signal Processing, Communications, & Computing (ICSPCC 2012) and the APSIPA Annual and Summit 2015, which were held in Hong Kong in August 2012 and December 2015, respectively. He was also a General Co-Chair of the 2017 IEEE International Conference on Multimedia and Expo, held in Hong Kong. He was the Chairman of the IEEE Hong Kong Chapter of Signal Processing between 2006 and 2008. He received an Honorable Mention of the Annual Pattern Recognition Society Award for an outstanding contribution to the Pattern Recognition Journal in 2004. In 2008, he also received the Best Paper Award at the International Conference on Neural Networks and Signal Processing.

He was the Chairman of the Student Services Committee and the Membership Services Committee of the IEEE Signal Processing Society between 2012 and 2014, and between 2015 and 2017, respectively. He was an Associate Editor of IEEE Trans. on Image Processing between 2009 and 2014, an Editor of HKIE Transactions between 2013 and 2018, and an Area Editor of the IEEE Signal Processing Magazine between 2015 and 2017. Currently, he is the VP-Publications of the Asia-Pacific Signal and Information Processing Association (APSIPA). He also serves as an Associate Editor of APSIPA Trans. on Signal and Information Processing, and EURASIP International Journal on Image and Video Processing. His current research interests include human face recognition, image and video processing, and computer vision.

4. Name: Ivor Tsang

Ivor W Tsang is an ARC Future Fellow and Professor of Artificial Intelligence, at University of Technology Sydney (UTS). He is also the Research Director of the UTS Flagship Research Centre for Artificial Intelligence (CAI) with more than 30 faculty members and 180 PhD students. His research focuses on transfer learning, feature selection, crowd intelligence, big data analytics for data with extremely high dimensions in features, samples and labels. He has more than 180 research papers published in top-tier journal and conference papers. In 2009, Prof Tsang was conferred the 2008 Natural Science Award (Class II) by Ministry of Education, China, which recognized his contributions to kernel methods. In 2013, Prof Tsang received his prestigious Australian Research Council Future Fellowship for his research regarding Machine Learning on Big Data. In addition, he had received the prestigious IEEE Transactions on Neural Networks Outstanding 2004 Paper Award in 2007, the 2014 IEEE Transactions on Multimedia Prize Paper Award, and a number of best paper awards and honors from reputable international conferences, including the Best Student Paper Award at CVPR 2010. He serves as an Associate Editor for the IEEE Transactions on Big Data, the IEEE Transactions on Emerging Topics in Computational Intelligence and Neurocomputing. He is serving as a Guest Editor for the special issue of “Structured Multi-output Learning: Modelling, Algorithm, Theory and Applications” in the IEEE Transactions on Neural Networks and Learning Systems. He serves as an Area Chair/Senior PC for NeurIPS, AISTATS, AAAI and IJCAI.

5. Name: Yongping Zheng

Professor Yongping Zheng has been serving as the Founding Head of the Department of Biomedical Engineering in The Hong Kong Polytechnic University (PolyU) since 2012. He has been appointed as Henry G. Leong Professor in Biomedical Engineering since July 2017. Professor Zheng received the BEng and MEng in Electronics and Information Engineering from the University of Science and Technology of China. He received PhD degree in Biomedical Engineering from PolyU in 1997. After a postdoctoral fellowship at the University of Windsor, Canada, he joined PolyU as an Assistant Professor and was promoted to Professor in 2008, and Chair Professor in 2019. He served as the Associate Director of the Research Institute of Innovative Products in PolyU from 2008 to 2010.

Prof. Zheng’s main research interests include biomedical ultrasound, 3D ultrasound imaging, soft tissue elasticity measurement and imaging, ultrasound neuromodulation, wearable sensors for healthcare and smart aging technologies. He is a Senior Member of IEEE, a Fellow of Hong Kong Institution of Engineers, Secretary of World Association of Chinese Biomedical Engineers (2017-2019). He has trained 12 PhD and 9 MPhil students, and over 10 postdoctoral fellows. He is currently supervising 8 PhD. He also owned around 50 patents, published 230 journal papers, and wrote a book “Measurement of Soft Tissue Elasticity In Vivo: Techniques and Applications”, several technologies invented by his team have been successfully commercialized, including Scolioscan (, an ultrasound device to provide radiation-free assessment of scoliosis. He also served as Associate Editor and Editorial Board Members for many journals.

6. Name: Timothy Lee

Timothy Tin Yan Lee gained his BEng (2010) and MSc (2011) in Biomedical Engineering from The University of Hong Kong and The Chinese University of Hong Kong, respectively. He just acquired his PhD and is now a postdoctoral fellow in the Hong Kong Polytechnic University. His research interest is 3D ultrasound imaging for adolescent idiopathic scoliosis (AIS), with his doctoral research focused on the analysis of the sagittal curvature of the spine of scoliosis patients. Using the novel 3D ultrasound imaging for spine, his recent work discovered the coupling effect between the coronal and sagittal curvatures and also confirmed the value of using the sagittal spinal profile for scoliosis curve progression. Currently he is working on the optimization of curvature measurement and three-dimensional analysis on curve progression of AIS patients using ultrasound, with the aim of providing clinical applications in the near future. Before starting his PhD, Mr Lee have obtained an MPhil in biomedical engineering from the Hong Kong Polytechnic University in 2014, focusing on the effect of whole body vibration on spinal proprioception of healthy subjects and patients with low back pain.