Evaluation of the risk of stroke with confidence predictions based on ultrasound carotid image analysis

International Journal on Artificial Intelligence Tools

Volumn 21, Issue 4, 2012, Pages

  Lambrou, Antonis ^a   Papadopoulos, Harris ^b   Kyriacou, Efthyvoulos ^b   Pattichis, Constantinos S ^c   Pattichis, Marios S ^d   Gammerman, Alexander ^a   Nicolaides, Andrew ^e,f,g  

^a UNIVERSITY OF LONDON   (United Kingdom)

^b FREDERICK UNIVERSITY   (Cyprus)

^c UNIVERSITY OF CYPRUS   (Cyprus)

^d MSC01 1070   (United States)

^e IMPERIAL COLLEGE LONDON   (United Kingdom)

^f Vascular Screening and Diagnostic Centre   (United Kingdom)

^g Cyprus Cardiovascular Disease Educational Research Trust   (Cyprus)

Author keywords

assessment of stroke risk; atherosclerotic carotid plaques; confidence measures; Conformal prediction; ultrasound image analysis

Indexed keywords

CAROTID PLAQUES; CLASSIFICATION METHODS; CONFIDENCE MEASURE; FEATURE SETS; IMAGE TEXTURE ANALYSIS; K-NEAREST NEIGHBOURS; MORPHOLOGICAL IMAGE ANALYSIS; NAIVE BAYES CLASSIFICATION; RISK-BASED; ULTRASOUND IMAGES;

FORECASTING; LEARNING ALGORITHMS; NEURAL NETWORKS; SUPPORT VECTOR MACHINES; ULTRASONICS;

IMAGE ANALYSIS;

EID: 84865746118     PISSN: 02182130     EISSN: 17936349     Source Type: Journal    
DOI: 10.1142/S0218213012400167     Document Type: Article

References (33)

1. Gianni Belcaro, Andrew N. Nicolaides, Giuseppe Laurora, Maria Rosaria Cesarone, Mariateresa De Sanctis, Lucrezia Incandela, and Antonio Barsotti. Ultrasound morphology classification of the arterial wall and cardiovascular events in a 6-year follow-up study. Arterioscler Thromb Vasc Biol, 16(7):851-856, 1996.
2. Tony Bellotti, Zhiyuan Luo, and Alexander Gammerman. Reliable classification of childhood acute leukaemia from gene expression data using confidence machines. In Proceedings of IEEE International Conference on Granular Computing (GRC '06), pages 148-153, 2006.
3. Tony Bellotti, Zhiyuan Luo, Alexander Gammerman, Frederick W. Van Delft, and Vaskar Saha. Qualified predictions for microarray and proteomics pattern diagnostics with confidence machines. International Journal of Neural Systems, 15(4):247-258, 2005.
4. Christodoulos I. Christodoulou, Efthyvoulos Kyriacou, Costantinos S. Pattichis, and Andrew Nicolaides. Multiple feature extraction for content-based image retrieval of carotid plaque ultrasound images. In Proceedings of the 5th International IEEE Special Topic Conference on Information Technology Applications in Biomedicine, pages 26-28, 2006.
5. C.I. Christodoulou, C.S. Pattichis, M. Pantziaris, and A. Nicolaides. Texture-based classification of atherosclerotic carotid plaques. IEEE Transactions on Medical Imaging, 22(7):902-912, 2003.
6. Devetyarov Dmitry and Nouretdinov Ilia. Prediction with confidence based on a ran-dom forest classifier. In Artificial Intelligence Applications and Innovations -6th IFIP WG 12.5 International Conference (AIAI 2010), volume 339, pages 37-44. Springer Boston, 2010.
7. N. El-Barghouty, G. Geroulakos, A. Nicolaides, A. Androulakis, and V. Bahal. Computer-assisted carotid plaque characterisation. European Journal of Vascular and Endovascular Surgery, 9(4):389-393, 1995.
8. A. Gammerman, V. Vovk, and V. Vapnik. Learning by transduction. In Uncertainty in Artificial Intelligence, pages 148-155. Morgan Kaufmann, 1998.
9. Alexander Gammerman, Ilia Nouretdinov, Brian Burford, Alexey Chervonenkis, Volodya Vovk, and Zhiyuan Luo. Clinical mass spectrometry proteomic diagnosis by conformal predictors. Statistical Applications in Genetics and Molecular Biology, 7(2), 2008.
10. G. Geroulakos, A. Domjan, A. Nicolaides, J. Stevens, N. Labropoulos, G. Ramaswami, and G. Belcaro. Ultrasonic carotid artery plaque structure and the risk of cere-bral infraction on computer tomography. Journal of Vascular Surgery, 20(2):263-266, 1994.
11. Arcangelo Iannuzzi, Timothy Wilcosky, Michele Mercuri, Paolo Rubba, Fred A. Bryan, and M. Gene Bond. Ultrasonographic correlates of carotid atherosclerosis in transient ischemic attack and stroke. Stroke, 26(4):614-619, 1995.
12. E.C. Kyriacou, C. Pattichis, M. Pattichis, C. Loizou, C. Christodoulou, S.K. Kakkos, and A. Nicolaides. A review of noninvasive ultrasound image processing methods in the analysis of carotid plaque morphology for the assessment of stroke risk. Information Technology in Biomedicine, IEEE Transactions on, 14(4):1027 -1038, 2010.
13. E.C. Kyriacou, C.S. Pattichis, M.A. Karaolis, C.P. Loizou, C.I. Christodoulou, M.S. Pattichis, S. Kakkos, and A. Nicolaides. An integrated system for assessing stroke risk. Engineering in Medicine and Biology Magazine, IEEE, 26(5):43-50, 2007.
14. Efthyvoulos Kyriacou, Marios S. Pattichis, Constantinos S. Pattichis, A. Mavrommatis, C. I. Christodoulou, S. Kakkos, and A. Nicolaides. Classification of atherosclerotic carotid plaques using morphological analysis on ultrasound images. Applied Intelli-gence, 30(1):3-23, 2009.
15. Antonis Lambrou, Harris Papadopoulos, and Alexander Gammerman. Reliable confidence measures for medical diagnosis with evolutionary algorithms. IEEE Transactions on Information Technology in Biomedicine, 15(1):93 -99, 2011.
16. Antonis Lambrou, Harris Papadopoulos, Efthyvoulos C. Kyriacou, Constantinos S. Pattichis, Marios S. Pattichis, Alexander Gammerman, and Andrew Nicolaides. Assessment of stroke risk based on morphological ultrasound image analysis with con-formal prediction. In Artificial Intelligence Applications and Innovations -6th IFIP WG 12.5 International Conference (AIAI 2010), pages 146-153, 2010.
17. M. Langsfeld, A.C. Gray-Weale, and R.J. Lusby. The role of plaque morphology and diameter reduction in the development of new symptoms in asymptomatic carotid arteries. Journal of Vascular Surgery, 9(4):548-557, 1989.
18. Thomas Melluish, Craig Saunders, Ilia Nouretdinov, and Volodya Vovk. Comparing the Bayes and Typicalness frameworks. In Proceedings of the 12th European Conference on Machine Learning (ECML'01), volume 2167 of Lecture Notes in Computer Science, pages 360-371. Springer, 2001.
19. Stavroula Gr. Mougiakakou, Spyretta Golemati, Ioannis Gousias, Andrew N. Nicolaides, and Konstantina S. Nikita. Computer-aided diagnosis of carotid atherosclerosis based on ultrasound image statistics, laws' texture and neural networks. Ultrasound in Medicine & Biology, 33(1):26 -36, 2007.
20. Andrew N. Nicolaides, Edward G. Shifrin, Andrew Bradbury, Surinder Dhanjil, Maura Griffin, Gianni Belcaro, and Michael Williams. Angiographic and duplex grading of internal carotid stenosis: Can we overcome the confusion? Journal of Endovascular Surgery, 3(2):158-165, 1996.
21. Ilia Nouretdinov, Volodya Vovk, Michael Vyugin, and Alex Gammerman. Pattern recognition and density estimation under the general i.i.d. assumption. In David Helm-bold and Bob Williamson, editors, Computational Learning Theory, volume 2111 of Lecture Notes in Computer Science, pages 337-353. Springer Berlin/Heidelberg, 2001.
22. Harris Papadopoulos. Inductive conformal prediction: Theory and application to neu-ral networks. In Paula Fritzsche, editor, Tools in Artificial Intelligence, chapter 18, pages 315-330. I-Tech, Vienna, Austria, 2008. URL http://www.intechopen.com/ download/pdf/pdfs id/5294.
23. Harris Papadopoulos, Alex Gammerman, and Volodya Vovk. Reliable diagnosis of acute abdominal pain with conformal prediction. Engineering Intelligent Systems, 17(2-3):115-126, 2009.
24. Harris Papadopoulos and Haris Haralambous. Reliable prediction intervals with regression neural networks. Neural Networks, 24(8):842-851, 2011.
25. Harris Papadopoulos, Kostas Proedrou, Volodya Vovk, and Alex Gammerman. Inductive confidence machines for regression. In Proceedings of the 13th European Conference on Machine Learning (ECML'02), volume 2430 of Lecture Notes in Computer Science, pages 345-356. Springer, 2002.
26. Harris Papadopoulos, Vladimir Vovk, and Alex Gammerman. Regression conformal prediction with nearest neighbours. Journal of Artificial Intelligence Research, 40:815-840, 2011. URL http://dx.doi.org/10.1613/jair.3198.
27. Harris Papadopoulos, Volodya Vovk, and Alex Gammerman. Qualified predictions for large data sets in the case of pattern recognition. In Proceedings of the 2002 International Conference on Machine Learning and Applications, pages 159-163, 2002.
28. Harris Papadopoulos, Volodya Vovk, and Alex Gammerman. Conformal prediction with neural networks. In Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'07), volume 2, pages 388-395. IEEE Computer Society, 2007.
29. Kostas Proedrou, Ilia Nouretdinov, Volodya Vovk, and Alex Gammerman. Transductive confidence machines for pattern recognition. In Proceedings of the 13th European Conference on Machine Learning (ECML'02), volume 2430 of Lecture Notes in Computer Science, pages 381-390. Springer, 2002.
30. Craig Saunders, Alex Gammerman, and Volodya Vovk. Transduction with confidence and credibility. In Proceedings of the 16th International Joint Conference on Artificial Intelligence, volume 2, pages 722-726, Los Altos, CA, 1999. Morgan Kaufmann.
31. Volodya Vovk, Alex Gammerman, and Craig Saunders. Machine-learning applications of algorithmic randomness. In Proceedings of the Sixteenth International Conference on Machine Learning, pages 444-453. Morgan Kaufmann, 1999.
32. Volodya Vovk, Alexander Gammerman, and G. Shafer. Algorithmic Learning in a Random World. New York, Springer, 2005.
33. J.E. Wilhjelm, M.-L.M. Gronholdt, B. Wiebe, S.K. Jespersen, L.K. Hansen, and H. Sillesen. Quantitative analysis of ultrasound b-mode images of carotid atheroscle-rotic plaque: correlation with visual classification and histological examination. IEEE Transactions on Medical Imaging, 17(6):910-922, 1998.