Medical Imaging Convention [rescheduled] Mar 09, 2021 - Mar 10, 2021 — National Exhibition Centre, Birmingham, England
9th SINAPSE Neuro-oncology Imaging Meeting [rescheduled] Mar 11, 2021 09:30 AM - 03:30 PM — West Park Conferencing & Events, 319 Perth Road, Dundee DD2 1NN
Total Body PET 2020 conference [rescheduled] Jun 05, 2021 - Jun 07, 2021 — McEwan Hall, University of Edinburgh

eLearning

SINAPSE experts from around Scotland have developed ten online modules designed to explain medical imaging. They are freely available and are intended for non-specialists.


Edinburgh Imaging Academy at the University of Edinburgh offers the following online programmes through a virtual learning environment:

Neuroimaging for Research MSc/Dip/Cert

Imaging MSc/Dip/Cert

PET-MR Principles & Applications Cert

Applied Medical Image Analysis Cert

Online Short Courses

A histogram-based similarity measure for quantitative magnetic resonance imaging: application in acute mild traumatic brain injury

Author(s): B. S. Aribisala, C. J. Cowie, J. He, J. Wood, D. A. Mendelow, P. Mitchell, A. M. Blamire

Abstract:
OBJECTIVES: The most commonly used summary metric in neuroimaging is the mean value, but this pays little attention to the shape of the data distribution and can therefore be insensitive to subtle changes that alter the data distribution. METHODS: We propose a distributional-based metric called the normalized histogram similarity measure (HSM) for characterization of quantitative images. We applied HSM to quantitative magnetic resonance imaging T1 relaxation data of 44 patients with mild traumatic brain injury and compared with data of 43 age-matched controls. RESULTS: Significant differences were found between the patients and the controls in 8 gray matter regions using the HSM whereas in only 1 gray matter region based on the mean values. CONCLUSIONS: Our results show that HSM is more sensitive than the standard mean values in detecting brain tissue changes. Future studies on brain tissue properties using quantitative magnetic resonance imaging should consider the use of HSM to properly capture any tissue changes.

Full version: Available here

Click the link to go to an external website with the full version of the paper


ISBN: 1532-3145 (Electronic) 0363-8715 (Linking)
Publication Year: 2014
Periodical: J Comput Assist Tomogr
Periodical Number: 6
Volume: 38
Pages: 915-23
Author Address: From the *Institute of Cellular Medicine & Newcastle Magnetic Resonance Centre, Newcastle University, Newcastle upon Tyne; daggerBrain Research Imaging Centre, University of Edinburgh, Edinburgh; double daggerInstitute of Neuroscience, Newcastle University, Newcastle upon Tyne; and section signDepartment of Neurosurgery, Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne, UK.