Bradley Ferguson

T-ray computed tomography

We demonstrate a tomographic imaging modality that uses pulsed terahertz (THz) radiation to probe the optical properties of three-dimensional (3D) structures in the far-infrared. This THz-wave computed tomography (T-ray CT) system provides sectional images of objects in a manner analogous to conventional CT techniques such as x-ray CT. The transmitted amplitude and phase of broadband pulses of THz radiation are measured at multiple projection angles. The filtered backprojection algorithm is then used to reconstruct the target object, including both its 3D structure and its frequency-dependent far-infrared optical properties.

T-Ray Sensing and Imaging

T-ray wavelengths are long enough to pass through dry, nonpolar objects opaque at visible wavelengths, but short enough to be manipulated by optical components to form an image. Sensing in this band potentially provides advantages in a number of areas of interest to security and defense such as screening of personnel for hidden objects and the retection of chemical and biological agents. Several private companies are developing smaller, reliable cheaper systems allowing for commercialization and this motivates us to review a number of promising applications within this paper. While there are a number of challenges to be overcome there is little doubt that T-ray technology will play a significant role in the near future for advancement of security, public health, and defense.

T-ray Imaging and Tomography.

We demonstrate two algorithms used forreconstructing the targets structure basedon the diffracted pulses and additionallyshow that a three-dimensional target can bereconstructed using the broadband pulsesand a Fresnel lens by virtue of itsfrequency dependent focal length. Oneadvantage of T-ray imaging is the abilityto measure the far-infrared spectralresponse of the target. To highlight theimportance of this spectral information, wedemonstrate T-ray classification imagingwith different biological samples using asimple classification algorithm and twodimensional T-ray spectroscopic images.

De-noising techniques for terahertz responses of biological samples

Abstract Signal processing techniques may be used to improve the speed, resolution and noise robustness of pulsed terahertz (T-ray) imaging systems. Such systems have a wide range of applications and much recent interest has focussed on several promising biomedical fields. There are a number of significant challenges to be overcome before a commercial biomedical terahertz system can be realised. Recent research is focussed on the implementation of a high speed, compact and portable T-ray imaging system. This system will draw heavily on MOEMS technology. One of the major stages in the development of such a system is the design of efficient software algorithms to perform signal recognition and imaging operations in real time. This paper considers a number of signal processing techniques suitable for de-noising and extracting information from the data obtained in a terahertz pulse imaging system. Two main de-noising techniques are considered. Wavelet de-noising and Wiener deconvolution algorithms are applied to the terahertz responses of biological samples including Spanish Serrano ham and an oak leaf.

Towards functional 3D T-ray imaging

We review the recent development of T-ray computed tomography, a terahertz imaging technique that allows the reconstruction of the three-dimensional refractive index profile of weakly scattering objects. Terahertz pulse imaging is used to obtain images of the target at multiple projection angles and the filtered backprojection algorithm enables the reconstruction of the objects frequency-dependent refractive index. The application of this technique to a biological bone sample and a plastic test structure is demonstrated. The structure of each target is accurately resolved and the frequency-dependent refractive index is determined. The frequency-dependent information may potentially be used to extract functional information from the target, to uniquely identify different materials or to diagnose medical conditions.

WAVELET DE-NOISING OF OPTICAL TERAHERTZ PULSE IMAGING DATA

Terahertz pulse imaging (TPI) systems are used to obtain sub-millimeter spectroscopic measurements for a wide range of applications. This letter highlights the use of wavelet de-noising to markedly improve the SNR of the obtained data, increasing the SNR by up to 10 dB. A comparison of different wavelet families and properties is presented and the results demonstrated on THz image data of an oak leaf and an Australian

Support Vector Machine Applications in Terahertz Pulsed Signals Feature Sets

100 note.

Wavelet based local tomographic image using terahertz techniques

In the past decade, terahertz radiation (T-rays) have been extensively applied within the fields of industrial and biomedical imaging, owing to their noninvasive property. Support vector machine (SVM) learning algorithms are sufficiently powerful to detect patterns hidden inside noisy biomedical measurements. This paper introduces a frequency orientation component method to extract T-ray feature sets for the application of two- and multiclass classification using SVMs. Effective discriminations of ribonucleic acid (RNA) samples and various powdered substances are demonstrated. The development of this method has become important in T-ray chemical sensing and image processing, which results in enhanced detectability useful for many applications, such as quality control, security detection and clinic diagnosis.

2-D Wavelet Segmentation in 3-D T-Ray Tomography

Terahertz computed tomography has been developed based on coherent THz detection and filtered back projection (FBP) algorithms, which allows the global imaging of the internal structure and extraction of the frequency dependent properties. It offers a promising approach for achieving non-invasive inspection of solid materials. However, with traditional CT techniques, i.e. FBP algorithms, full exposure data are needed for inverting the Radon transform to produce cross sectional images. This remains true even if the region of interest is a small subset of the entire image. For time-domain terahertz measurements, the requirement for full exposure data is impractical due to the slow measurement process. This paper explores time domain reconstruction of terahertz measurements by applying wavelet-based filtered back projection algorithms for recovery of a local area of interest from terahertz measurements within its vicinity, and thus improves the feasibility of using terahertz imaging to detect defects in solid materials and diagnose disease states for clinical practise, to name a few applications.

A Systemized View of Superluminal Wave Propagation

In this letter, segmentation techniques for terahertz (T-ray) computed tomographic (CT) imaging are investigated. A set of linear image fusion and novel wavelet scale correlation segmentation techniques is adopted to achieve material discrimination within a 3-D object. The methods are applied to a T-ray CT image dataset taken from a plastic vial containing a plastic tube. This setup simulates the imaging of a simple nested organic structure, which provides an indication of the potential for using T-ray CT imaging to achieve T-ray pulsed signal classification of heterogeneous layers