Dual-mode photoacoustic and ultrasound imaging system based on a Fabry-Pérot scanner

The planar Fabry-Pérot (FP) scanner is an ultrasound detector that simultaneously provides high sensitivity, a high density of small (sub-100 μm) acoustic elements, and a broad bandwidth (> 30 MHz). These features enable the FP scanner to acquire high-resolution 3D in vivo photoacoustic images of biological tissues up to depths of approximately 10 mm. The aim was to add complementary morphological ultrasound contrast to photoacoustic images to extend their clinical applicability. This was achieved by developing a dual-mode photoacoustic and ultrasound imaging system based on the FP scanner, which was modified to transmit optically generated ultrasound. The FP sensor head was coated with an optically absorbing polydimethylsiloxane(PDMS) composite layer, which was excited with nanosecond laser pulses to generate broadband planar ultrasound waves for pulse-echo imaging. First, an all-optical ultrasound system was developed using a highly absorbing carbon nanotube-PDMS composite coating. The system was characterised with a series of experiments, and its imaging performance was tested on tissue mimicking phantoms and ex vivo tissue samples. Second, the effect of the frequency content of the detected signals and the effect of spatial aliasing on the image quality were investigated in simulation. A broadband system was found to reduce the effect of spatial undersampling of high frequencies which results in a reduction of contrast due to the formation of grating lobe artefacts. Third, to improve the image quality, frequency and angle compounding were explored in simulations and experimentally. Coherent and incoherent compounding were considered, as well as the effect of the filter bandwidth on frequency compounded images, and the influence of the number and spread of angles used in angle compounded images. Finally, a dual- mode photoacoustic and ultrasound imaging system was demonstrated with a gold nanoparticle-PDMS composite which enabled wavelength-selective absorption of light. The system was shown to obtain high-resolution 3D dual-mode images providing complementary contrast from optically absorbing and acoustically scattering structures

Single-cell diffraction tomography with optofluidic rotation about a tilted axis

Optical diffraction tomography (ODT) is a tomographic technique that can be used to measure the three-dimensional (3D) refractive index distribution within living cells without the requirement of any marker. In principle, ODT can be regarded as a generalization of optical projection tomography which is equivalent to computerized tomography (CT). Both optical tomographic techniques require projection-phase images of cells measured at multiple angles. However, the reconstruction of the 3D refractive index distribution post-measurement differs for the two techniques. It is known that ODT yields better results than projection tomography, because it takes into account diffraction of the imaging light due to the refractive index structure of the sample. Here, we apply ODT to biological cells in a microfluidic chip which combines optical trapping and microfluidic flow to achieve an optofluidic single-cell rotation. In particular, we address the problem that arises when the trapped cell is not rotating about an axis perpendicular to the imaging plane, but instead about an arbitrarily tilted axis. In this paper we show that the 3D reconstruction can be improved by taking into account such a tilted rotational axis in the reconstruction process.Comment: 7 pages, 3 figure

New implementations of phase-contrast imaging

Phase-contrast imaging is a method of imaging widely used in biomedical research and applications. It is a label-free method that exploits intrinsic differences in the refractive index of different tissues to differentiate between biological structures under analysis. The basic principle of phase-contrast imaging has inspired a lot of implementations that are suited for different applications. This thesis explores multiple novel implementations of phase-contrast imaging in the following order. 1, We combined scanning Oblique Back-illumination Microscope (sOBM) and confocal microscope to produce phase and fluorescence contrast images in an endomicroscopy configuration. This dual-modality design provides co-registered, complementary labeled and unlabeled contrast of the sample. We further miniaturized the probe by dispensing the two optical fibers in our old design. And we presented proof of principle demonstrations with ex-vivo mouse colon tissue. 2, Then we explored sOBM-based phase and amplitude contrast imaging under different wavelengths. Hyperspectral imaging is achieved by multiplexing a wide-range supercontinuum laser with a Michaelson interferometer (similar to Fourier transform spectroscopy). It features simultaneous acquisition of hyperspectral phase and amplitude images with arbitrarily thick scattering biological samples. Proof-of-principle demonstrations are presented with chorioallantoic membrane of a chick embryo, illustrating the possibility of high-resolution hemodynamics imaging in thick tissue. 3, We focused on increasing the throughput of flow cytometry with principle of phase-contrast imaging and compressive sensing. By utilizing the linearity of scattered patterns under partially coherent illumination, our cytometer can detect multiple objects in the same field of view. By utilizing an optimized matched filter on pupil plane, it also provides increased information capacity of each measurement without sacrificing speed. We demonstrated a throughput of over 10,000 particles/s with accuracy over 91% in our results. 4, A fourth part, which describes the principle and preliminary results of a computational fluorescence endomicroscope is also included. It uses a numerical method to achieve sectioning effect and renders a pseudo-3D image stack with a single shot. The results are compared with true-3D image stack acquired with a confocal microscope

Reconstructions in limited-view thermoacoustic tomography

The limited-view problem is studied for thermoacoustic tomography, which is also referred to as photoacoustic or optoacoustic tomography depending on the type of radiation for the induction of acoustic waves. We define a “detection region,” within which all points have sufficient detection views. It is explained analytically and shown numerically that the boundaries of any objects inside this region can be recovered stably. Otherwise some sharp details become blurred. One can identify in advance the parts of the boundaries that will be affected if the detection view is insufficient. If the detector scans along a circle in a two-dimensional case, acquiring a sufficient view might require covering more than a π-, or less than a π-arc of the trajectory depending on the position of the object. Similar results hold in a three-dimensional case. In order to support our theoretical conclusions, three types of reconstruction methods are utilized: a filtered backprojection (FBP) approximate inversion, which is shown to work well for limited-view data, a local-tomography-type reconstruction that emphasizes sharp details (e.g., the boundaries of inclusions), and an iterative algebraic truncated conjugate gradient algorithm used in conjunction with FBP. Computations are conducted for both numerically simulated and experimental data. The reconstructions confirm our theoretical predictions

Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)

The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between international scientific teams by disseminating ideas through both specific oral/poster presentations and free discussions. For its second edition, the iTWIST workshop took place in the medieval and picturesque town of Namur in Belgium, from Wednesday August 27th till Friday August 29th, 2014. The workshop was conveniently located in "The Arsenal" building within walking distance of both hotels and town center. iTWIST'14 has gathered about 70 international participants and has featured 9 invited talks, 10 oral presentations, and 14 posters on the following themes, all related to the theory, application and generalization of the "sparsity paradigm": Sparsity-driven data sensing and processing; Union of low dimensional subspaces; Beyond linear and convex inverse problem; Matrix/manifold/graph sensing/processing; Blind inverse problems and dictionary learning; Sparsity and computational neuroscience; Information theory, geometry and randomness; Complexity/accuracy tradeoffs in numerical methods; Sparsity? What's next?; Sparse machine learning and inference.Comment: 69 pages, 24 extended abstracts, iTWIST'14 website: http://sites.google.com/site/itwist1

Plenoptic Signal Processing for Robust Vision in Field Robotics

This thesis proposes the use of plenoptic cameras for improving the robustness and simplicity of machine vision in field robotics applications. Dust, rain, fog, snow, murky water and insufficient light can cause even the most sophisticated vision systems to fail. Plenoptic cameras offer an appealing alternative to conventional imagery by gathering significantly more light over a wider depth of field, and capturing a rich 4D light field structure that encodes textural and geometric information. The key contributions of this work lie in exploring the properties of plenoptic signals and developing algorithms for exploiting them. It lays the groundwork for the deployment of plenoptic cameras in field robotics by establishing a decoding, calibration and rectification scheme appropriate to compact, lenslet-based devices. Next, the frequency-domain shape of plenoptic signals is elaborated and exploited by constructing a filter which focuses over a wide depth of field rather than at a single depth. This filter is shown to reject noise, improving contrast in low light and through attenuating media, while mitigating occluders such as snow, rain and underwater particulate matter. Next, a closed-form generalization of optical flow is presented which directly estimates camera motion from first-order derivatives. An elegant adaptation of this "plenoptic flow" to lenslet-based imagery is demonstrated, as well as a simple, additive method for rendering novel views. Finally, the isolation of dynamic elements from a static background is considered, a task complicated by the non-uniform apparent motion caused by a mobile camera. Two elegant closed-form solutions are presented dealing with monocular time-series and light field image pairs. This work emphasizes non-iterative, noise-tolerant, closed-form, linear methods with predictable and constant runtimes, making them suitable for real-time embedded implementation in field robotics applications