Special Issue "Selected Papers from “MIUA 2017”"

A special issue of Journal of Imaging (ISSN 2313-433X).

Deadline for manuscript submissions: closed (7 November 2017)

Special Issue Editors

Guest Editor
Dr. Maria del C. Valdés Hernández

Lecturer in Image Analysis and Chair MIUA 2017 Centre for Clinical Brain Sciences (CCBS), Neuroimaging Sciences, The University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
Website | E-Mail
Interests: brain; image analysis; cerebrovascular diseases; neurodegenerative diseases
Guest Editor
Dr. Victor Gonzalez-Castro

Department of Electrics, Systems and Automatics Engineering,Universidad de León. Campus de Vegazana s/n, 24071 León, Spain
Website | E-Mail
Interests: image analysis; pattern recognition; machine learning; medical imaging

Special Issue Information

Dear Colleagues,

Medical Image Understanding and Analysis (MIUA) 2017 (https://miua2017.wordpress.com/) is the 21st 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 medical image processing and analysis and aims to encourage the growth and raise the profile of this multi-disciplinary field by bringing together specialists, academics, engineers, image analysts and clinicians from various communities, including human body, lung, brain and cardiac imaging, pre-clinical, microscopy and animal images, medical physics, anatomy, physiology, oncology, dermatology, neurology, radiology, ophtalmology, ultrasound, magnetic resonance, positron emission imaging, and computed tomography among others.

The conference covers the following topics in the field of medical imaging: Big Data Processing, Clinical and Scientific Evaluation of Imaging Studies, Computer-Aided Pathology, Computer-Aided Radiology, Computer-Assisted Surgery, Data Fusion, Data Compression and Anonimisation, Protocol Development and Standardisation, Decision Support, Discovery of Imaging Biomarkers, Human Computer Interaction, Image Interpretation, Image-Guided Intervention, Image Formation and Reconstruction, Image Perception, Image Registration, Image Segmentation, Intelligent Imaging Systems, Machine Learning in Medical Imaging, Modelling and Simulation, Motion Analysis, Multi-Modality Image Analysis, Pattern and Feature Recognition, Quantitative Image Analysis, Shape Analysis, Software Development, Super-Resolution Algorithms, Statistical Methods in Imaging, Systematic Testing and Validation, Texture Analysis, Image Enhancement, Time series analyses and Virtual Reality Visualisation.

The conference constitutes an excellent opportunity to network, generate new ideas, establish new collaborations, learn and discuss on different topics, listen to proferred speakers of international reputation, present and show medical image analysis software and even experience the delights of a genuine Scottish ceilidh.

Dr. Maria del C. Valdés Hernández
Dr. Victor Gonzalez-Castro
Guest Editors


Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Imaging is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) is waived for well-prepared manuscripts submitted to this issue. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • Medical image analysis
  • Machine learning
  • Magnetic resonance imaging
  • Microscopy
  • Positron emission imaging
  • Ultrasound

Published Papers

This special issue is now open for submission, see below for planned papers.

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Restoration of Bi-contrast MRI Data for Intensity Uniformity with Bayesian Coring of Co-occurrence Statistics
Author: Stathis Hadjidemetriou
Abstract: The reconstruction in MRI assumes a uniform radio-frequency field. However, this is violated, which leads to anatomically inconsequential intensity non-uniformities. An anatomic region can be imaged with multiple contrasts and suffer from different non-uniformities. These artifacts can complicate further image analysis. A method is presented for the joint intensity uniformity restoration of two such images. The effect of the intensity distortion on the auto-co-occurrence statistics of each image as well as on the joint-co-occurrence statistics of the two images is modeled. Their Bayesian non-stationary deconvolution gives coring estimates of the images. Further constraints for smoothness and stability of the non-uniformity estimates are imposed. Moreover, the method considers the inevitable difference between the valid signal regions of the two images. The joint restoration of the two images can improve accuracy and efficiency. The effectiveness of the method has been demonstrated extensively with both the BrainWeb phantom as well as with real brain anatomic data of Parkinson’s disease patients.
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