High-resolution and high-sensitivity blood flow estimation using optimization approaches with application to vascularization imaging
| Autor: | Adrian Basarab, C. Barthelemy, Y. Zemmoura, H. Shen, Denis Kouame, E. Khoury, J.-P. Remenieras |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
business.industry
Computer science Pattern recognition 02 engineering and technology Blood flow Filter (signal processing) Inverse problem 030218 nuclear medicine & medical imaging 03 medical and health sciences symbols.namesake 0302 clinical medicine Computer Science::Computer Vision and Pattern Recognition Singular value decomposition 0202 electrical engineering electronic engineering information engineering Filtering problem symbols Clutter 020201 artificial intelligence & image processing Deconvolution Sensitivity (control systems) Artificial intelligence business Doppler effect Robust principal component analysis |
| Zdroj: | 2019 IEEE International Ultrasonics Symposium (IUS). |
| DOI: | 10.1109/ultsym.2019.8925840 |
| Popis: | In this paper, we address the problem of high-resolution flow estimation in medical ultrasound images. Imaging methods based on ultrafast sequences associated with adaptive spatiotemporal SVD clutter filtering have recently improved blood flow detection. Herein, we investigate a new way of addressing the clutter filtering problem in order to obtain a high-resolution flow estimation, through solving an inverse problem corresponding to both deconvolution and robust principal component analysis. Applied to tissue vascularization imaging via power Doppler images, the proposed method highlights finer details on experimental data compared to existing approaches. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|