Graduate Seminar

Graduate Seminar
November, 19, 2018
in Room 1061 Electrical Eng. Building Technion City

Gilad Drozdov

Viterbi Faculty of Electrical Engineering, Technion


Optoacoustic tomography with negatively focused detectors

Optical imaging is an essential tool for biological discovery with growing clinical applications. One of the fundamental challenges in performing optical imaging at depths above 1 mm is that light scattering by tissue heterogeneity leads to loss of spatial coherence. Accordingly, deep-tissue optical imaging is characterized by diffusive light propagation and low resolution. Optoacoustic tomography (OAT) is a hybrid imaging modality that enables visualizing optical absorption with typical ultrasound resolutions in the diffusive regime of light. In OAT, the excitation is performed by pulse light, whereas the detection is of ultrasound. Because the optoacoustic effect is weak, deep-tissue imaging often requires using detectors significantly larger than the acoustic wavelength, often at the price of reduced tangential resolution. Negatively focused (NF) detectors have been shown to mitigate the loss of resolution while achieving high sensitivity. Commonly, image reconstruction with NF detectors is performed by using the virtual-detector approach, which does not accurately account for the detector geometry, leading to image artifacts. In this talk, we present a theoretical study on the effect negatively focused detectors have on OAT image reconstruction. As part of our study, we developed analytical time-domain expressions for the spatially dependent impulse response of NF detectors in two and three dimensions, supplemented by asymptotic expressions in the frequency domain. Our analysis elucidates the working principle behind the virtual-detector approximation and the origin of image artifacts when this approximation is used. While the principle behind the virtual detector approach is valid for both two- and three-dimensional imaging scenarios, we show that the artifacts associated with it are of different nature. Based on our analysis, we introduce a simple correction to the virtual-detector approximation that significantly enhances image contrast and reduces artifacts.

M.Sc. student under the advisement of assistant Prof. Amir Rosenthal.