Photoacoustic tomography and sensing in biomedicine

Photoacoustics has been broadly studied in biomedicine, for both human and small animal tissues. Photoacoustics uniquely combines the absorption contrast of light or radio frequency waves with ultrasound resolution. Moreover, it is non-ionizing and non-invasive, and is the fastest growing new biomedical method, with clinical applications on the way. This review provides a brief recap of recent developments in photoacoustics in biomedicine, from basic principles to applications. The emphasized areas include the new imaging modalities, hybrid detection methods, photoacoustic contrast agents and the photoacoustic Doppler effect, as well as translational research topics

Mathematics and Algorithms in Tomography

This was the ninth Oberwolfach conference on the mathematics of tomography. Modalities represented at the workshop included X-ray tomography, radar, seismic imaging, ultrasound, electron microscopy, impedance imaging, photoacoustic tomography, elastography, emission tomography, X-ray CT, and vector tomography along with a wide range of mathematical analysis

Photoacoustic Tomography: Principles and Advances

Photoacoustic tomography (PAT) is an emerging imaging modality that shows great potential for preclinical research and clinical practice. As a hybrid technique, PAT is based on the acoustic detection of optical absorption from either endogenous chromophores, such as oxy-hemoglobin and deoxy-hemoglobin, or exogenous contrast agents, such as organic dyes and nanoparticles. Because ultrasound scatters much less than light in tissue, PAT generates high-resolution images in both the optical ballistic and diffusive regimes. Over the past decade, the photoacoustic technique has been evolving rapidly, leading to a variety of exciting discoveries and applications. This review covers the basic principles of PAT and its different implementations. Strengths of PAT are highlighted, along with the most recent imaging results

Microwave imaging for security applications

Microwave imaging technologies have been widely researched in the biomedical field where they rely on the imaging of dielectric properties of tissues. Healthy and malignant tissue have different dielectric properties in the microwave frequency region, therefore, the dielectric properties of a human body’s tissues are generally different from other contraband materials. Consequently, dielectric data analysis techniques using microwave signals can be used to distinguish between different types of materials that could be hidden in the human body, such as explosives or drugs. Other concerns raised about these particular imaging systems were how to build them cost effectively, with less radiation emissions, and to overcome the disadvantages of X-ray imaging systems. The key challenge in security applications using microwave imaging is the image reconstruction methods adopted in order to gain a clear image of illuminated objects inside the human body or underneath clothing. This thesis will discuss in detail how microwave tomography scanning could overcome the challenge of imaging objects concealed in the human body, and prove the concept of imaging inside a human body using image reconstruction algorithms such as Radon transformation image reconstruction. Also, this thesis presents subspace based TR-MUSIC algorithms for point targets and extended targets. The algorithm is based on the collection of the dominant response matrix reflected by targets at the transducers in homogenous backgrounds, and uses the MUSIC function to image it. Lumerical FDTD solution is used to model the transducers and the objects to process its response matrix data in Matlab. Clear images of metal dielectric properties have been clearly detected. Security management understanding in airports is also discussed to use new scanning technologies such as microwave imaging in the future.The main contribution of this reseach is that microwave was proved to be able to image and detect illegal objects embedded or implanted inside human body

Assessing data acquisition approaches in electron tomography

Electron tomography (ET) is a technique to reveal the interior structures of organic-subcellular macro molecules- and inorganic materials from their 2D cross sectional transmission electron microscope (TEM) projections. However, restricted radiation dose due to specimen damage and blind region of angular sampling as a result of physical constraints deteriorate the quality of the resultant tomograms. Typically, electron tomograms suffer from low signal to noise ratio (SNR) and elongation artifact in the direction of electron radiation. Different studies propose methods to tackle the constraints of ET in the data acquisition stage. This thesis is a comparative study among different data acquisition models by analyzing the resultant tomogram of each method quantitatively. We implement each model with a TEM simulator and compare the tomograms by their root mean square (RMS) and resolution. Results of TEM settings indicate that 1) reducing the acceleration voltage and increasing the defocus value intensifies the contrast. 2) Diminishing the objective diaphragm size reduces the brightness of the projections. Comparing data acquisition models states that 1) cosine model of dose distribution homogenizes the SNR of sinograms and compared to the conventional methods enhances the resolution of the tomograms. 2) Employing Saxton model for angular sampling boosts the resolution and declines the elongation artifact. 3) Combination of the cosine method of dose distribution and Saxton's model promotes the resolution, RMS value and elongation artifact significantly: resolution enhanced 1.81 times compared to the constant dose and angle distribution models in Z-direction. To conclude, emphasis on the SNR and sampling frequency of highly tilted angles outperforms the conventional data acquisition approaches qualitatively and quantitatively

Photoacoustic imaging in biomedicine

Photoacoustic imaging (also called optoacoustic or thermoacoustic imaging) has the potential to image animal or human organs, such as the breast and the brain, with simultaneous high contrast and high spatial resolution. This article provides an overview of the rapidly expanding field of photoacoustic imaging for biomedical applications. Imaging techniques, including depth profiling in layered media, scanning tomography with focused ultrasonic transducers, image forming with an acoustic lens, and computed tomography with unfocused transducers, are introduced. Special emphasis is placed on computed tomography, including reconstruction algorithms, spatial resolution, and related recent experiments. Promising biomedical applications are discussed throughout the text, including (1) tomographic imaging of the skin and other superficial organs by laser-induced photoacoustic microscopy, which offers the critical advantages, over current high-resolution optical imaging modalities, of deeper imaging depth and higher absorptioncontrasts, (2) breast cancerdetection by near-infrared light or radio-frequency–wave-induced photoacoustic imaging, which has important potential for early detection, and (3) small animal imaging by laser-induced photoacoustic imaging, which measures unique optical absorptioncontrasts related to important biochemical information and provides better resolution in deep tissues than optical imaging

Sonar systems for object recognition

The deep sea exploration and exploitation is one of the biggest challenges of the next century. Military, oil & gas, o shore wind farming, underwater mining, oceanography are some of the actors interested in this eld. The engineering and technical challenges to perform any tasks underwater are great but the most crucial element in any underwater systems has to be the sensors. In air numerous sensor systems have been developed: optic cameras, laser scanner or radar systems. Unfortunately electro magnetic waves propagate poorly in water, therefore acoustic sensors are a much preferred tool then optical ones. This thesis is dedicated to the study of the present and the future of acoustic sensors for detection, identi cation or survey. We will explore several sonar con gurations and designs and their corresponding models for target scattering. We will show that object echoes can contain essential information concerning its structure and/or composition