RiiSE20 Conference [postponed] Apr 04, 2020 08:30 AM - 05:00 PM — Chancellor’s Building, Edinburgh BioQuarter
Scottish Clinical Imaging Network (SCIN) Annual Event 2020 [postponed] Apr 30, 2020 09:00 AM - 04:00 PM — Glasgow Caledonian University
NCITA National Conference: Translating Imaging Biomarkers for Improved Patient Outcomes [postponed] May 05, 2020 10:00 AM - 05:00 PM — New Hunt's House, Guy's Campus, King's College London
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2020 SINAPSE ASM Jun 19, 2020 09:00 AM - 05:00 PM — Virtual Meeting (online)

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

Detection of New Vessels on the Optic Disc Using Retinal Photographs

Author(s): K. A. Goatman, A. D. Fleming, S. Philip, G. J. Williams, J. A. Olson, P. F. Sharp

Abstract:
Proliferative diabetic retinopathy is a rare condition likely to lead to severe visual impairment. It is characterized by the development of abnormal new retinal vessels. We describe a method for automatically detecting new vessels on the optic disc using retinal photography. Vessel-like candidate segments are first detected using a method based on watershed lines and ridge strength measurement. Fifteen feature parameters, associated with shape, position, orientation, brightness, contrast and line density are calculated for each candidate segment. Based on these features, each segment is categorized as normal or abnormal using a support vector machine (SVM) classifier. The system was trained and tested by cross-validation using 38 images with new vessels and 71 normal images from two diabetic retinal screening centers and one hospital eye clinic. The discrimination performance of the fifteen features was tested against a clinical reference standard. Fourteen features were found to be effective and used in the final test. The area under the receiver operator characteristic curve was 0.911 for detecting images with new vessels on the disc. This accuracy may be sufficient for it to play a useful clinical role in an automated retinopathy analysis system.

Full version: Available here

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


ISBN: 0278-0062
Publication Year: 2011
Periodical: Ieee Transactions on Medical Imaging
Periodical Number: 4
Volume: 30
Pages: 972-979
Author Address: Goatman, KA Univ Aberdeen, Div Appl Med, Sch Med & Dent, Aberdeen AB25 2ZD, Scotland Univ Aberdeen, Div Appl Med, Sch Med & Dent, Aberdeen AB25 2ZD, Scotland Grampian Diabet Retinal Screening Programme, Aberdeen AB25 2ZP, Scotland Univ Aberdeen, Sch Med Sci, Aberdeen AB25 2ZD, Scotland