Scottish Radiological Society Spring Meeting 2021 May 14, 2021 09:00 AM - 05:00 PM — Virtual Meeting (online)
9th Annual Scottish Radiotherapy Research Forum Jun 03, 2021 12:30 PM - 05:00 PM — Virtual Meeting (online)
Medical Imaging Convention [rescheduled] Sep 15, 2021 - Sep 16, 2021 — National Exhibition Centre, Birmingham, England
Total Body PET 2021 conference [rescheduled] Sep 25, 2021 - Sep 27, 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

Lesion Area Detection Using Source Image Correlation Coefficient for CT Perfusion Imaging

Author(s): F. Zhu, D. R. Gonzalez, T. Carpenter, M. Atkinson, J. Wardlaw

Abstract:
Computer tomography (CT) perfusion imaging is widely used to calculate brain hemodynamic quantities such as cerebral blood flow, cerebral blood volume, and mean transit time that aid the diagnosis of acute stroke. Since perfusion source images contain more information than hemodynamic maps, good utilization of the source images can lead to better understanding than the hemodynamic maps alone. Correlation-coefficient tests are used in our approach to measure the similarity between healthy tissue time-concentration curves and unknown curves. This information is then used to differentiate penumbra and dead tissues from healthy tissues. The goal of the segmentation is to fully utilize information in the perfusion source images. Our method directly identifies suspected abnormal areas from perfusion source images and then delivers a suggested segmentation of healthy, penumbra, and dead tissue. This approach is designed to handle CT perfusion images, but it can also be used to detect lesion areas in magnetic resonance perfusion images.

Full version: Available here

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


ISBN: 2168-2194
Publication Year: 2013
Periodical: Ieee Journal of Biomedical and Health Informatics
Periodical Number: 5
Volume: 17
Pages: 950-958
Author Address: Zhu, F Univ Edinburgh, Sch Informat, Data Intens Res Grp, Edinburgh EH8 9AB, Midlothian, Scotland Univ Edinburgh, Sch Informat, Data Intens Res Grp, Edinburgh EH8 9AB, Midlothian, Scotland Univ Edinburgh, Div Clin Neurosci, Brain Res Imaging Ctr, Edinburgh EH4 2XU, Midlothian, Scotland