Yerevan, Yerevan 0014
Ultrasound is one of the most common medical imaging techniques, with clinical applications such as pregnancy monitoring, cardiology or cancer detection. Ultrasound images result from the interaction between an ultrasound wave emitted by the scanner probe and the human tissues.
In this series of three lectures, I will review the basics of ultrasound image formation, as well as two signal and image processing related applications adapted to ultrasound imaging.
- Lecture 1 - Introduction to ultrasound medical imaging: The first part of this lecture will address generalities on medical imaging techniques. The rest of the talk will focus on ultrasound. It will mainly concern two topics, the physics of ultrasound and the ultrasound image formation from a signal processing viewpoint.
- Lecture 2 - Inverse problems in ultrasound imaging: Inverse problems are one of the most explored topics in signal and image processing, in connection with applied mathematics. A few examples will help understanding the concept of inverse problems and the main related technical difficulties. In the second part of the lecture, two typical inverse problems applied to ultrasound imaging will be addressed: compressive sampling and deconvolution.
- Lecture 3 - Phase-based motion estimation in ultrasound imaging: Tissue motion estimation is a common application in medical imaging, with applications such as cardiology or cancer detection. In ultrasound imaging, the noisy nature of the images makes the tissue motion estimation very challenging. One way to deal with this problem is to use spatial phase images. In this lecture, I will show the different ways to transform images in phase images and the way they can be exploited for motion estimation.
Presenter: Dr. Adrian Basarab (France) received the M.S. and PhD degrees in signal and image processing from the National Institute for Applied Sciences of Lyon, France, in 2005 and 2008. Since 2009 he is assistant professor at the University Paul Sabatier Toulouse 3 and a member of IRIT laboratory (UMR CNRS 5505). His research interests include medical imaging, and more particularly motion estimation, inverse problems and u! ltrasoun d image formation. Adrian Basarab is currently member of the French National Council of Universities Section 61 - Computer sciences, Automatic Control and Signal
Please be aware that the number of participants is limited.
The tutorial is orginized within the INARMERA-ICT (Integrating Armenia into ERA: Information and and Communication Technologies) Project funded by the EU Seventh Framework Programme.
Ultrasound is one of the most common medical imaging techniques, with clinical applications such as pregnancy monitoring, cardiology or cancer detection. Ultrasound images result from the interaction between an ultrasound wave emitted by the scanner probe and the human tissues.
In this series of three lectures, I will review the basics of ultrasound image formation, as well as two signal and image processing related applications adapted to ultrasound imaging.
- Lecture 1 - Introduction to ultrasound medical imaging: The first part of this lecture will address generalities on medical imaging techniques. The rest of the talk will focus on ultrasound. It will mainly concern two topics, the physics of ultrasound and the ultrasound image formation from a signal processing viewpoint.
- Lecture 2 - Inverse problems in ultrasound imaging: Inverse problems are one of the most explored topics in signal and image processing, in connection with applied mathematics. A few examples will help understanding the concept of inverse problems and the main related technical difficulties. In the second part of the lecture, two typical inverse problems applied to ultrasound imaging will be addressed: compressive sampling and deconvolution.
- Lecture 3 - Phase-based motion estimation in ultrasound imaging: Tissue motion estimation is a common application in medical imaging, with applications such as cardiology or cancer detection. In ultrasound imaging, the noisy nature of the images makes the tissue motion estimation very challenging. One way to deal with this problem is to use spatial phase images. In this lecture, I will show the different ways to transform images in phase images and the way they can be exploited for motion estimation.
Presenter: Dr. Adrian Basarab (France) received the M.S. and PhD degrees in signal and image processing from the National Institute for Applied Sciences of Lyon, France, in 2005 and 2008. Since 2009 he is assistant professor at the University Paul Sabatier Toulouse 3 and a member of IRIT laboratory (UMR CNRS 5505). His research interests include medical imaging, and more particularly motion estimation, inverse problems and u! ltrasoun d image formation. Adrian Basarab is currently member of the French National Council of Universities Section 61 - Computer sciences, Automatic Control and Signal
Please be aware that the number of participants is limited.
The tutorial is orginized within the INARMERA-ICT (Integrating Armenia into ERA: Information and and Communication Technologies) Project funded by the EU Seventh Framework Programme.