Call for Abstracts
Deadline: April 1, 2019
23rd Medical Image Analysis and Understanding Conference
July 24-26, 2018, Liverpool, United Kingdom
MIUA 2019 is the 23rd conference of the Medical Image Understanding and Analysis series organised in the United Kingdom for communicating research progress in biomedical image analysis. Its goals are the dissemination and discussion of research in medical image processing and analysis. All researchers in medical image analysis are encouraged to attend, including mathematicians, computer scientists, bioinformaticians, clinicians, engineers and bioscientists. Together, we aim to encourage growth and raise the profile of this multi-disciplinary field. The conference features keynote speakers, tutorials, workshops, and oral and poster presentations.
Authors are invited to submit medical imaging-related abstract for MIUA 2019. This includes:
- Clinical Abstracts
- Modelling and Artificial Intelligence
- Device Development
- Software Development
- Pre-clinical Imaging
- Bio-science Imaging
- Signal Processing
- Challenge Abstracts
- Diagnostic Models
Abstracts should be written using the template provided here.
Completed abstracts can be submitted to email@example.com. Abstracts should be up to one page of A4 (including tables and figures), using Calibri font size 11, and structured to include:
- Authors and Affiliations
- Background and Purpose
- Discussion and/or Conclusion
- References and Acknowledgements if applicable
Submission Deadline: 1 April 2019
How can I submit an abstract to MIUA?
Please submit your one-page abstracts to firstname.lastname@example.org.
Paper Submissions are now closed but you are welcome to submit an abstract to MIUA2019.
Authors are invited to submit full papers of length between 8 and 12 pages (1 column – LNCS Springer format) showing original research contributions in medical image analysis and processing. The conference proceedings will be published in the Springer CCIS – Communications in Computer and Information Science and there will be a special issue in the Journal of Imaging for selected papers.
Submission Deadline: 4 March 2019
How can I submit a paper to MIUA?
Please submit your paper at https://ocs.springer.com/ocs/home/MIUA2019:
- Click on Submit Abstract
- Enter the Title and Keywords for your paper
- Copy your abstract in the Abstract box
- Enter the names, e-mail addresses and affiliations of your authors
- Upload your manuscript by clicking the “Choose File” button next to “Paper Document (PDF)”
- Click “Submit Abstract”
I have just uploaded my abstract for MIUA. Do I need to upload the paper now or wait for a decision on the abstract?
Please upload your abstract when you upload the paper. The abstract and paper will be reviewed together.
Invited Keynote Speakers
We have five exciting keynote talks planned from leaders in the field of medical imaging from the University of North Caroline, Cambridge University, Universität Freiburg,
Paper Submission Opens: November 30, 2018
Paper Submission Deadline: March 4, 2019
Abstract Submission Deadline: April 1, 2019
Author Notification: April 15, 2019
Camera-ready papers due: April 26, 2019
Early-bird registration due: April 28, 2019
Conference: July 24-26, 2019
We will precede MIUA with a two-day Workshop on Image Processing Techniques and Applications, which can be booked separately or alongside the conference. MIUA will take place Wednesday-Friday and, on Saturday, we are planning a social/ networking event at the Snowdonia National Park.
22-23 July 2019: IPTA 2019
24-26 July 2019: MIUA 2019
27 July 2019: Social/ Networking Event
|Big data processing
Clinical and Scientific Evaluation of Imaging Studies
Data compression and anonymisation
Discovery of imaging biomarkers
Human Computer Interaction
Image formation and reconstruction
|Intelligent Imaging Systems
Machine Learning in Imaging
Modelling and Simulation
Multi-Modality Image Analysis
Pattern and feature recognition
Protocol Development and Standardization
Quantitative Image Analysis
Statistical Methods in Imaging
Systematic Testing & Validation
Time series analyses