Abstract
An ultrasound imaging technique providing sub-diffraction limit axial resolution for point sources is proposed. It is based on simultaneously acquired multi-focal images of the same object, and on the image metric of sharpness. The sharpness is extracted by image data and presents higher values for in-focus images. The technique is derived from biological microscopy and is validated here with simulated ultrasound data. A linear array probe is used to scan a point scatterer phantom that moves in depth with a controlled step. From the beamformed responses of each scatterer position the image sharpness is assessed. Values from all positions plotted together form a curve that peaks at the receive focus, which is set during the beamforming. Selection of three different receive foci for each acquired dataset will result in the generation of three overlapping sharpness curves. A set of three calibration curves combined with the use of a maximum-likelihood algorithm is then able to estimate, with high precision, the depth location of any emitter fron each single image. Estimated values are compared with the ground truth demonstrating that an accuracy of 28.6 μm (0.13λ) is achieved for a 4 mm depth range.
Original language | English |
---|---|
Title of host publication | 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015 |
Publisher | IEEE |
Pages | 7067-7070 |
Number of pages | 4 |
ISBN (Print) | 9781424492718 |
DOIs | |
Publication status | Published - 4 Nov 2015 |
Event | 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2015 - Milan, Italy Duration: 25 Aug 2015 → 29 Aug 2015 |
Conference
Conference | 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2015 |
---|---|
Abbreviated title | EMBC 2015 |
Country/Territory | Italy |
City | Milan |
Period | 25/08/15 → 29/08/15 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Signal Processing
- Biomedical Engineering
- Health Informatics