MIUA 2020 - CALL FOR PAPERS (Extended Deadline: 31st March 2020)

24th MEDICAL IMAGE UNDERSTANDING AND ANALYSIS CONFERENCE

15th - 17th July 2020, Oxford, United Kingdom

MIUA 2020 is the 24th conference of the Medical Image Understanding and Analysis series organised in the United Kingdom for communicating research progress within the community interested in biomedical image analysis. Its goals are the dissemination and discussion of research in biomedical image analysis and machine learning and aims to encourage the growth and raise the profile of this multi-disciplinary field.
The conference features keynote speakers, oral and poster presentations.

KEYNOTE SPEAKERS:
MIUA2020 will host three exciting keynote talks from leaders in the field of machine learning and medical imaging:
Micheal Bronstein, Chair in Machine Learning and Pattern Recognition, Imperial College London
Julia A. Schnabel, Chair in Computational Imaging, King’s College London
Fergus Gleeson, Professor of Radiology and Consultant Radiologist, University of Oxford

WORKSHOPS:
MIUA2020 will host two workshops:
The University of Oxford’s Visual Geometry Group (VGG) will demonstrate state-of-the-art deep learning tools in object tracking, detection and retrieval.
MathWorks engineers will demonstrate the latest MATLAB Deep Learning tools for medical image analysis.

PAPER SUBMISSIONS:
Authors are invited to submit full papers of length between 8 and 12 pages (1 column - the CCIS template) showing original research contributions under the topics of the conference.
All accepted full papers will be published as a volume in the Springer Communications in Computer and Information Science (CCIS).


IMPORTANT DATES:
Paper Submission opens: January 2020
Paper Submission deadline: 17th March 2020
Author Notification: 28th April 2020
Camera-ready papers due: 8th May 2020
Early-bird registration due: 15th May 2020
Conference: July 15th-17th, 2020


CONFERENCE TOPICS:
Big data processing
Clinical and Scientific Evaluation of Imaging Studies
Computer-Aided Pathology
Computer-Aided Radiology
Computer-Assisted Surgery
Data compression and anonymization Data Fusion
Decision Support Discovery of imaging biomarkers
Human Computer Interaction
Image Enhancement
Image Interpretation
Image-Guided Intervention
Image formation and reconstruction
Image Perception
Image Registration
Image Segmentation
Intelligent Imaging Systems
Machine Learning in Imaging Modelling and Simulation
Motion Analysis
Multi-Modality Image Analysis
Pattern and feature recognition
Protocol Development and Standardisation
Quantitative Image Analysis
Shape Analysis
Software development
Super-resolution algorithms
Statistical Methods in Imaging
Systematic Testing & Validation
Texture Analysis
Time series analyses
Virtual Reality
Visualisation

FURTHER INFORMATION:
Webpage: http://miua2020.com/
Email: miua2020 (at) eng.ox.ac.uk
Twitter: @miua2020ox