Project title: "Super Resolution algorithms and software tools for MR imaging techniques"
Collaborating institution: Institute of Biomedical Engineering, Boğaziçi University (Turkey)
About the project
A vast amount of radiological data is currently considered suboptimal, and is archived without further use due to their poor spatial resolution and sometimes low quality. Subtle indications of early disease stages are also missed for the same reason. The spatial resolution choice is about finding a good balance between image quality, voxel size and acquisition time. This project aims to deliver computational methods and software tools to increase the resolution of different modalities of magnetic resonance images (MRI) to ensure better brain research, diagnosis and timely treatment strategies.
Initially funded by the Royal Society Newton Mobility Grant in 2016, this collaboration is ongoing due to synergies in research interests,
Institute of Biomedical Engineering, Boğaziçi University (Turkey)
The University of Edinburgh (UK)
Professor Esin Ozturk Isik
Contact email address: Esin.Ozturk@boun.edu.tr
Contact email address: email@example.com
Research Assistant, PhD Candidate
Contact email address: firstname.lastname@example.org
Dr Maria Valdes-Hernandez
Row Fogo Lecturer in Medical Image Analysis
Contact email address: M.Valdes-Hernan@ed.ac.uk
Ozturk-Isik E, Marshall I, Filipiak P, Benjamin AJ, Ones VG, Ramón RO, Valdés Hernández MD. Workshop on reconstruction schemes for magnetic resonance data: summary of findings and recommendations. R Soc Open Sci. 2017;4(2):160731.
Sevim Cengiz, Maria del C. Valdes-Hernandez, Ozturk-Isik E. Super Resolution Convolutional Neural Networks for Increasing Spatial Resolution of 1H Magnetic Resonance Spectroscopic Imaging. Medical Image Understanding and Analysis 2017, Communications in Computer and Information Science, Vol. 723, pp.641-650, Springer, 2017. ISSN 1865-0929. Invited and Research Talks
Invited conference talks and scientific workshops
Sevim Cengiz, Maria del C. Valdes-Hernandez, Ozturk-Isik E. Super Resolution Convolutional Neural Networks for Increasing Spatial Resolution of 1H Magnetic Resonance Spectroscopic Imaging. Medical Image Understanding and Analysis 2017 conference, 13th July 2017.
Cengiz, S. Advances in magnetic resonance spectroscopic image processing. ‘Recent Advances in Magnetic Resonance Imaging’ workshop, Bogazici University, Istanbul, June 20th, 2017.
Ozturk-Isik E. Compressed Sensing for Fast 31P-MRSI of Brain Tumors and 1H-MRSI of Mild Cognitive Impairment in Parkinson’s Disease. ‘Reconstruction schemes for MR data' workshop, University of Edinburgh, UK, August 17th, 2016
Please, get in touch with Dr Maria Valdes-Hernandez in case of