JIFS2019: Special Issue on Fuzzy Systems for Medical Image Analysis |
Submission link | https://easychair.org/conferences/?conf=jifs2019 |
Abstract registration deadline | December 31, 2019 |
Submission deadline | December 31, 2019 |
The modern imaging devices capable of acquiring data rapidly with a high resolution has led to a considerable gain of medical images over the recent years. The interpretation of medical images is mostly by a physician, nevertheless, information technology supported image interpretation is an area of increasing interest. Many diagnostic tasks need an initial search process to find any abnormalities, evaluate the measurements, and quantify the changes over time. The process of interpretation of a medical image by a human is essentially affected by subjectivity, a deviation of results across interpreters, and fatigue. The computational algorithms, inspired by Artificial Intelligence and Machine Learning, have much to offer in the handling of the inherent uncertainties involved in the medical image interpretation process. In particularly, the fuzzy methods, by virtue of their non-statistical-uncertainty handling capabilities, could serve as effective tools in the field of medical imaging and informatics. Due to a large heterogeneity and complexity, it is required to determine representations of clinical awareness from big imaging data for better understanding of health informatics.
Fuzzy methodology is rapidly becoming the state of the art, leading to enhanced performance in various medical applications and digital approaches to prevent, diagnose, and treat diseases. How the fuzzy based systems could contribute towards next generation imaging based diagnostic systems is the main topic of the current section.
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
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Potential topics included, but not limited to:
- Fuzzy image processing for diseases diagnosis
- Fuzzy integration of Imaging and Clinical data
- Fuzzy wavelet extreme learning methods in medical image analysis
- Fuzzy mathematical programming in medical image analysis
- Fuzzy classification for multi-modality image fusion for analysis, diagnosis, and intervention
- Fuzzy modelling for molecular / pathologic / cellular image analysis
- Fuzzy dynamic, functional and physiologic imaging
- Other fuzzy modelling methods in diseases diagnosis
- Fuzzy systems learning for prognosis and treatment selection
- Fuzzy modelling based telemedicine system
- Fuzzy modelling in medical imaging, including segmentation/ interpretation
Committees
Program Committee
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Prof.Dr.Weiping Zhang
Electronic and Information Engineering
Nanchang University,Xuefu Road 999, Nanchang, China
zhangweiping@ncu.edu.cnVice Dean
Binhai Industrial Technology Research Institute of Zhejiang University,
Gaoxin 6 road 39 Binhai Hi-tech Zone Tianjin, China
zhangweiping@zjubh.com
Dr.Rokhsareh Akbarzadeh
Department of Mechanical Engineering,
University of Johannesburg, Auckland Park
E-mail: rakbarzadeh@uj.ac.za,Rokhsareh.akbarzadeh@gmail.com,
Organizing committee
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Prof.Dr.Weiping Zhang
Electronic and Information Engineering
Nanchang University,Xuefu Road 999, Nanchang, China
zhangweiping@ncu.edu.cnVice Dean
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Binhai Industrial Technology Research Institute of Zhejiang University,
Gaoxin 6 road 39 Binhai Hi-tech Zone Tianjin, China
zhangweiping@zjubh.com
Dr.Rokhsareh Akbarzadeh
Department of Mechanical Engineering,
University of Johannesburg, Auckland Park
E-mail: rakbarzadeh@uj.ac.za, Rokhsareh.akbarzadeh@gmail.com,
Contact
All questions about submissions should be emailed to 20022415@sau.edu.cn