Terahertz cancer imaging and sensing: open research challenges and opportunities

被引:6
|
作者
Gezimati, Mavis [1 ]
Singh, Ghanshyam [1 ]
机构
[1] Univ Johannesburg, Ctr Smart Informat & Commun Syst, Dept Elect & Elect Engn Sci, POB 524, Auckland Pk Kingsway Campus, ZA-2006 Johannesburg, South Africa
关键词
Cancer detection; Challenges; Merits; Terahertz technology; Terahertz imaging and sensing; Biomedical application; Research opportunities; Recent trends; SPECTROSCOPY; TISSUE; DIAGNOSIS; SKIN; RECONSTRUCTION; MODEL;
D O I
10.1007/s11082-023-04991-7
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
There has been a rapid development of THz technology-sources, detectors and various THz imaging and sensing techniques. The THz technology demonstrates great potential as a modality for early, label free, non-ionizing and non-invasive detection of cancer. Some progressive technological development milestones have been achieved in this regard, however, to become clinically competitive and to provide the sought after real operational convenience, there is need for further research and development to overcome the existing challenges. This paper provides recent trends and perspectives through identification of existing challenges for the development of THz imaging and sensing systems that can evolve into actual medical modalities. We provide an overview of various aspects of THz technology, including techniques for imaging and sensing, mechanisms for THz image contrast and models for tissue dielectric responses to THz waves. The THz imaging application for detection of various cancers is briefed. The advantages of THz cancer imaging and sensing as well as the existing challenges are identified, with recommendations provided in contribution to future research. Further, some recent THz imaging and sensing developments such as the near-field methods to break the diffraction limit including waveguides, resonance and plasmonic metasurfaces are discussed. We emphasize the contribution of analytical algorithms that are based on machine learning, in particular, deep learning for the development of THz technology.
引用
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页数:33
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