Terahertz Computed Tomography System for in vivo Medical Imaging Applications

Terahertz (THz) technology is growing rapidly due to its variety of potential applications in security, sensing, biotech pharmacy, wireless communication, industrial inspection as well as material characterization. Because most chemicals have distinctive resonant modes in THz frequency range (0.1 – 10 THz), unique capabilities of non-destructive sensing based on THz spectrometry bring an exceptional platform for standoff tomographic scanning of many concealed chemicals, explosives, pharmaceutical materials, semiconductor structures and defects, and biological agents in real-time. However, the practical feasibility of THz imaging systems is severely limited by the low efficiency and bulky nature of active THz devices. Until now, THz imaging systems have still been utilized in research settings yet to be broadly used as consumer products. In the meanwhile, due to insufficient signal-to-noise ratio (SNR) and narrow bandwidth of current THz imaging systems, it is very challenging to achieve high-precision three-dimensional terahertz imaging with a decent scanning time.

This PhD project will target to develop a high-precision (especially superresolulation), rapid-scanning terahertz CT system based on ultrabroadband plasmonic photoconductive THz devices combined with advanced fast numerical algorithms. By utilizing state-of-the-art THz sources and detectors, the SNR of the proposed THz CT imaging system can potentially achieve several orders of magnitude higher than the conventional THz imaging systems over an extended spectral range of 0.1 – 10 THz. In addition to de-noising and quality enhancement, the PhD candidate will pursue two ideas in reducing scanning time and still maintaining high resolutions: (i) employ variational models to merge low resolution images in an optimal way so that the high resolution is achieved through functional representation; (ii) use advanced reproducing kernel Hilbert space representation to push up resolution. Hence, this system will offer deep penetration depth, high spatial resolution and abundant material information simultaneously due to the significantly reduced number of measurements required. The same idea can be applied to time point requisition. This will result in a much faster scanning speed compared with traditional scanning method. Such a high-precision, rapid-scanning THz imaging system delivers revolutionary impacts on current THz technology, which opens new research opportunities in biological sensing, pharmaceutical imaging, food inspection, industry inspection, quality control and gene engineering.

As Part of the NTHU-UoL Dual PhD Award students are in the unique position of being able to gain 2 PhD awards at the end of their degree from two internationally recognized world leading Universities. As well as benefiting from a rich cultural experience, Students can draw on large scale national facilities of both countries and create a worldwide network of contacts across 2 continents.

For enquiries please contact Prof. Ke Chen ([Email Address Removed]) or Prof. Shang-Hua Yang ([Email Address Removed]).

Applicants will have a first class or upper second class honours degree (or equivalent) in the engineering/science program and laboratory research experience. Successful candidates will have strong math and programming skills, ideally either from a Maths based degree with some skills in programming or an EEE / computer science degree with strong maths background.

An additional masters level research experience in terahertz technology, computer vision or medical imaging research is a benefit, though not required. All applicants must satisfy the appropriate University English language requirements. For EU and international students this is an IELTS score of 6.5 with no band score lower than 5.5.

When applying please ensure you Quote the supervisor & project title you wish to apply for and note ‘NTHU-UoL Dual Scholarship’ when asked for details of how plan to finance your studies. Be sure to send your CV, cover letter and the names and addresses of at least two references to [Email Address Removed].