TY - GEN
T1 - Radon transform technique for linear structures detection
T2 - 2011 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2011
AU - Tavakoli, M.
AU - Mehdizadeh, A. R.
AU - Pourreza, R.
AU - Pourreza, H. R.
AU - Banaee, T.
AU - Bahreini Toosi, M. H.
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2011
Y1 - 2011
N2 - In medical images linear patterns such as blood vessels are important structures for computer-aided diagnosis and follow-up of many diseases. Moreover, image processing techniques are required to extract suitable information about vascular tree and its alteration. Analyzing of retinal blood vessel is critical work for the investigation of some diseases. In this study, we present an automated method for detecting retinal vasculatures based upon Radon transform. In preprocessing, we used top-hat transformation and averaging filter. Our main processing was included applying Radon transform, vessel certifying, and vessel refinement. Comparing the results of our method with gold standard showed that our results have more than 93% for true positive rate. In conclusion, it is possible to use Radon transform for vessel segmentation in fluorescein angiography fundus images, with acceptable sensitivity and specificity, as a necessary step in some diagnostic algorithm for retinal pathology.
AB - In medical images linear patterns such as blood vessels are important structures for computer-aided diagnosis and follow-up of many diseases. Moreover, image processing techniques are required to extract suitable information about vascular tree and its alteration. Analyzing of retinal blood vessel is critical work for the investigation of some diseases. In this study, we present an automated method for detecting retinal vasculatures based upon Radon transform. In preprocessing, we used top-hat transformation and averaging filter. Our main processing was included applying Radon transform, vessel certifying, and vessel refinement. Comparing the results of our method with gold standard showed that our results have more than 93% for true positive rate. In conclusion, it is possible to use Radon transform for vessel segmentation in fluorescein angiography fundus images, with acceptable sensitivity and specificity, as a necessary step in some diagnostic algorithm for retinal pathology.
UR - http://www.scopus.com/inward/record.url?scp=84858638534&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84858638534&partnerID=8YFLogxK
U2 - 10.1109/NSSMIC.2011.6152552
DO - 10.1109/NSSMIC.2011.6152552
M3 - Conference contribution
AN - SCOPUS:84858638534
SN - 9781467301183
T3 - IEEE Nuclear Science Symposium Conference Record
SP - 3051
EP - 3056
BT - 2011 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2011
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 23 October 2011 through 29 October 2011
ER -