Total Body PET 2021 conference [rescheduled] Sep 22, 2021 - Sep 24, 2021 — Virtual Meeting (online)
PET is Wonderful Annual Meeting 2021 Oct 26, 2021 12:00 AM — Virtual Meeting (online)
NRS Mental Health Network Annual Scientific Meeting 2021 Nov 02, 2021 09:00 AM - 05:00 PM — Royal College of Physicians, Edinburgh (and online)


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

SINAPSE Image of the Month: OCTA retinal image segmentation

February 2021 SINAPSE Image of the Month


Courtesy of Ylenia Giarratano, Dr Tom MacGillivray and Dr Miguel Bernabeu, this image shows an original optical coherence tomography angiography (OCTA) image of the retina (left panel) acquired with the RTVue-XR Avanti OCT system, and the performance of three automated image segmentation methods used to perform vessel enhancement and binarization (right panels): an optimally oriented flux (OOF) handcrafted filter and two deep learning architectures, U-Net and CS-Net. Evaluation metrics applied to automated segmentation results for retinal scan subimages from 11 individuals found the best performance was achieved by U-Net and CS-Net architectures, and identified OOF as the best handcrafted filter for applications where manually segmented data are not available to retrain those approaches. The source code and the image dataset with associated ground truth manual segmentations have been made openly available to support standardization efforts in OCTA image segmentation.


The image is taken from a recent study published in Translational Vision Science & Technology:

Giarratano Y, Bianchi E, Gray C, Morris A, MacGillivray T, Dhillon B, Bernabeu MO. Automated Segmentation of Optical Coherence Tomography Angiography Images: Benchmark Data and Clinically Relevant Metrics. Transl Vis Sci Technol 2020; 9(13):5.