Computer Vision and Artificial Intelligence in Biomedical Image Analysis
Techniques of computer vision combined with paradigms of artificial intelligence have been increasingly proposed to accomplish automated analysis of objects represented in images. From the numerous possible application areas where the automated analysis of images can be found, the Biomedical area is predominant as those techniques can be used since the imaging acquisition to the diagnosis making.
However, the automated analysis of Biomedical images is challenging as it usually embraces complex tasks such as of image segmentation, matching and registration, motion/deformation tracking, classification, and reconstruction. For example, in the computer-aided diagnosis of an organ, like the heart, from a medical images sequence, first the input images should be segmented, then suitable features of the organ under analysis should be extracted and tracked along the images and finally, the tracked motion should be analyzed and the diagnosis can be made based on an artificial classifier.
In this talk, techniques of computer vision that we have developed combined with techniques of artificial intelligence to analyze objects in biomedical images are going to be introduced; particularly, those developed for image segmentation, matching, registration, tracking, classification and 3D shape reconstruction. Furthermore, their use in several biomedical applications will be presented and discussed.
References
“Techniques of Medical Image Processing and Analysis accelerated by High-Performance Computing: A Systematic Literature Review”, C.A.S.J. Gulo, A.C. Sementille, J.M.R.S. Tavares, Journal of Real-Time Image Processing 16(6):1891-1908, 2019
“Computational methods for the image segmentation of pigmented skin lesions: A Review”, R.B. Oliveira, M.E. Filho, Z. Ma, J.P. Papa, A.S. Pereira, J.M.R.S. Tavares, Computer Methods and Programs in Biomedicine 131:127-141, 2016
“Computational Methods for Pigmented Skin Lesion Classification in Images: Review and Future Trends”, R.B. Oliveira, J.P. Papa, A.S. Pereira, J.M.R.S. Tavares, Neural Computing and Applications 29(3):613-636, 2018
“Automatic 3D pulmonary nodule detection in CT images: a survey”, I.R.S. Valente, P.C. Corte, E.C. Neto, J.M. Soares, V.H.C. de Albuquerque, J.M.R.S. Tavares, Computer Methods and Programs in Biomedicine 124:91-107, 2016
“A review of computational methods applied for identification and quantification of atherosclerotic plaques in images”, D.S. Jodas, A.S. Pereira, J.M.R.S. Tavares, Expert Systems with Applications 46:1-14, 2016
“Segmentation Algorithms for Ear Image Data towards Biomechanical Studies”, A. Ferreira, F. Gentil, J.M.R.S. Tavares, Computer Methods in Biomechanics and Biomedical Engineering 17(8):888-904, 2014
“Medical Image Registration: a Review”, F.P.M. Oliveira, J.M.R.S. Tavares, Computer Methods in Biomechanics and Biomedical Engineering 17(2): 73-93, 2014
“A Review of Algorithms for Medical Image Segmentation and their Applications to the Female Pelvic Cavity”,
Z. Ma, J.M.R.S. Tavares, R.N. Jorge, T. Mascarenhas, Computer Methods in Biomechanics and Biomedical Engineering 13(2):235-246, 2010
“Image Processing and Analysis: Applications and Trends”, J.M.R.S. Tavares, AES-ATEMA’2010 Fifth International Conference, pp. 27-41, Montreal & Quebec City, Canada, 2010
However, the automated analysis of Biomedical images is challenging as it usually embraces complex tasks such as of image segmentation, matching and registration, motion/deformation tracking, classification, and reconstruction. For example, in the computer-aided diagnosis of an organ, like the heart, from a medical images sequence, first the input images should be segmented, then suitable features of the organ under analysis should be extracted and tracked along the images and finally, the tracked motion should be analyzed and the diagnosis can be made based on an artificial classifier.
In this talk, techniques of computer vision that we have developed combined with techniques of artificial intelligence to analyze objects in biomedical images are going to be introduced; particularly, those developed for image segmentation, matching, registration, tracking, classification and 3D shape reconstruction. Furthermore, their use in several biomedical applications will be presented and discussed.
References
“Techniques of Medical Image Processing and Analysis accelerated by High-Performance Computing: A Systematic Literature Review”, C.A.S.J. Gulo, A.C. Sementille, J.M.R.S. Tavares, Journal of Real-Time Image Processing 16(6):1891-1908, 2019
“Computational methods for the image segmentation of pigmented skin lesions: A Review”, R.B. Oliveira, M.E. Filho, Z. Ma, J.P. Papa, A.S. Pereira, J.M.R.S. Tavares, Computer Methods and Programs in Biomedicine 131:127-141, 2016
“Computational Methods for Pigmented Skin Lesion Classification in Images: Review and Future Trends”, R.B. Oliveira, J.P. Papa, A.S. Pereira, J.M.R.S. Tavares, Neural Computing and Applications 29(3):613-636, 2018
“Automatic 3D pulmonary nodule detection in CT images: a survey”, I.R.S. Valente, P.C. Corte, E.C. Neto, J.M. Soares, V.H.C. de Albuquerque, J.M.R.S. Tavares, Computer Methods and Programs in Biomedicine 124:91-107, 2016
“A review of computational methods applied for identification and quantification of atherosclerotic plaques in images”, D.S. Jodas, A.S. Pereira, J.M.R.S. Tavares, Expert Systems with Applications 46:1-14, 2016
“Segmentation Algorithms for Ear Image Data towards Biomechanical Studies”, A. Ferreira, F. Gentil, J.M.R.S. Tavares, Computer Methods in Biomechanics and Biomedical Engineering 17(8):888-904, 2014
“Medical Image Registration: a Review”, F.P.M. Oliveira, J.M.R.S. Tavares, Computer Methods in Biomechanics and Biomedical Engineering 17(2): 73-93, 2014
“A Review of Algorithms for Medical Image Segmentation and their Applications to the Female Pelvic Cavity”,
Z. Ma, J.M.R.S. Tavares, R.N. Jorge, T. Mascarenhas, Computer Methods in Biomechanics and Biomedical Engineering 13(2):235-246, 2010
“Image Processing and Analysis: Applications and Trends”, J.M.R.S. Tavares, AES-ATEMA’2010 Fifth International Conference, pp. 27-41, Montreal & Quebec City, Canada, 2010
João Manuel R. S. Tavares graduated in Mechanical Engineering at the Universidade do Porto, Portugal in 1992. He also earned his M.Sc. degree and Ph.D. degree in Electrical and Computer Engineering from the Universidade do Porto in 1995 and 2001, and attained his Habilitation in Mechanical Engineering in 2015. He is a senior researcher at the Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial (INEGI) and Associate Professor at the Department of Mechanical Engineering (DEMec) of the Faculdade de Engenharia da Universidade do Porto (FEUP).
João Tavares is co-editor of more than 55 books, co-author of more than 50 book chapters, 650 articles in international and national journals and conferences, and 3 international and 3 national patents. He has been a committee member of several international and national journals and conferences, is co-founder and co-editor of the book series “Lecture Notes in Computational Vision and Biomechanics” published by Springer, founder and Editor-in-Chief of the journal “Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization” published by Taylor & Francis, Editor-in-Chief of the journal “Computer Methods in Biomechanics and Biomedical Engineering” published by Taylor & Francis, and co-founder and co-chair of the international conference series: CompIMAGE, ECCOMAS VipIMAGE, ICCEBS and BioDental. Additionally, he has been (co-)supervisor of several MSc and PhD thesis and supervisor of several post-doc projects, and has participated in many scientific projects both as researcher and as scientific coordinator.
His main research areas include computational vision, medical imaging, computational mechanics, scientific visualization, human-computer interaction and new product development.
(More information can be found at: www.fe.up.pt/~tavares)
Prof. João Manuel R. S. Tavares
Faculdade de Engenharia da Universidade do Porto, Portugal
Email: [email protected]
url: www.fe.up.pt/~tavares
ORCID: http://orcid.org/0000-0001-7603-6526
João Tavares is co-editor of more than 55 books, co-author of more than 50 book chapters, 650 articles in international and national journals and conferences, and 3 international and 3 national patents. He has been a committee member of several international and national journals and conferences, is co-founder and co-editor of the book series “Lecture Notes in Computational Vision and Biomechanics” published by Springer, founder and Editor-in-Chief of the journal “Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization” published by Taylor & Francis, Editor-in-Chief of the journal “Computer Methods in Biomechanics and Biomedical Engineering” published by Taylor & Francis, and co-founder and co-chair of the international conference series: CompIMAGE, ECCOMAS VipIMAGE, ICCEBS and BioDental. Additionally, he has been (co-)supervisor of several MSc and PhD thesis and supervisor of several post-doc projects, and has participated in many scientific projects both as researcher and as scientific coordinator.
His main research areas include computational vision, medical imaging, computational mechanics, scientific visualization, human-computer interaction and new product development.
(More information can be found at: www.fe.up.pt/~tavares)
Prof. João Manuel R. S. Tavares
Faculdade de Engenharia da Universidade do Porto, Portugal
Email: [email protected]
url: www.fe.up.pt/~tavares
ORCID: http://orcid.org/0000-0001-7603-6526