Early detection of brain cancers biomedical sensor with low losses and high sensitivity in the terahertz regime based on photonic crystal fiber technology

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. Graphical abstract

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Terahertz cancer imaging and sensing: open research challenges and opportunities

Gezimati

Singh

2023

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Mixed integer programming with kriging surrogate model technique for dispersion control of photonic crystal fibers

Hammad,

Hameed,

Obayya

et al. 2023

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In this paper, mixed integer nonlinear programming (MINLP) optimization algorithm integrated with kriging surrogate-model is newly formulated to optimize the dispersion characteristics of photonic crystal fibers (PCFs). The MINLP is linked with full vectorial finite difference method (FVFDM) to optimize the modal properties of the PCFs. Through the optimization process, the design parameters can take real and/or integer values. The integer values can be used to selectively fill the PCF air holes to control its dispersion characteristics. However, the other optimization techniques deal with real design parameters where the PCF can be optimized using none or predefined infiltrated air holes. The MINLP algorithm is used to obtain an ultra-flat zero dispersion over a broadband of wavelength range from 1.25 to 1.6 μm using silica PCF selectively infiltrated with Ethanol material. To show the superiority of the proposed algorithm, nematic liquid crystal selectively infiltrated PCFs are also designed with high negative flat dispersion over wide range of wavelengths from 1.25 to 1.6 μm for the quasi transverse magnetic (TM) and the quasi transverse electric (TE) modes. Such designs have negative flat dispersions of − 163 ± 0.9 and − 170 ± 1.2 ps/Km nm, respectively over the studied wavelength range. Therefore, the MINLP algorithms could be used efficiently for the design and optimization of selectively filled photonic devices.

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Ultrasensitive Photonic Crystal Fiber Sensor for Identifying Various Explosives

et al. 2023

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Early detection of brain cancers biomedical sensor with low losses and high sensitivity in the terahertz regime based on photonic crystal fiber technology

Cited by 9 publications

References 66 publications

Terahertz cancer imaging and sensing: open research challenges and opportunities

Terahertz cancer imaging and sensing: open research challenges and opportunities

Mixed integer programming with kriging surrogate model technique for dispersion control of photonic crystal fibers

Ultrasensitive Photonic Crystal Fiber Sensor for Identifying Various Explosives

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