Co-registered combined OCT and THz imaging to extract depth and refractive index of a tissue-equivalent test object

Fitzgerald, Anthony J.; Tie, Xin; Hackmann, Michael J.; Cense, Barry; Gibson, Adam; Wallace, Vincent P.

doi:10.1364/boe.378506

Cited by 17 publications

(7 citation statements)

References 40 publications

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“…Terahertz imaging can provide unique information about the absorption properties of fresh tissue, but often lacks information about the tissue structure. Like many other established medical imaging modalities, terahertz imaging can be combined with other techniques to elucidate more information, for example, Fan et al combined terahertz with polarised optical images to delineate margins of skin cancer [255], and Fitzgerald et al have shown that terahertz and optical coherence tomography can be combined to extract depth resolved properties of samples [256].…”

Section: Advances In Science and Technology To Meet Challengesmentioning

confidence: 99%

The 2023 terahertz science and technology roadmap

Dhillon¹,

Vitiello²,

Linfield³

et al. 2023

J. Phys. D: Appl. Phys.

229

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Terahertz (THz) radiation encompasses a wide spectral range within the electromagnetic spectrum that extends from microwaves to the far infrared (100 GHz to ~30 THz). Within its frequency boundaries exist a broad variety of scientific disciplines that have presented, and continue to present, technical challenges to researchers. During the past 50 years, for instance, the demands of the scientific community have substantially evolved and with a need for advanced instrumentation to support radio astronomy, Earth observation, weather forecasting, security imaging, telecommunications, non-destructive device testing and much more. Furthermore, applications have required an emergence of technology from the laboratory environment to production-scale supply and in-the-field deployments ranging from harsh ground-based locations to deep space. In addressing these requirements, the research and development community has advanced related technology and bridged the transition between electronics and photonics that high frequency operation demands. The multidisciplinary nature of THz work was our stimulus for creating the 2017 THz Science and Technology Roadmap (S S Dhillon et al 2017 J. Phys. D: Appl. Phys. 50 043001). As one might envisage, though, there remains much to explore both scientifically and technically and the field has continued to develop and expand rapidly. It is timely, therefore, to revise our previous roadmap and in this 2023 version we both provide an update on key developments in established technical areas that have important scientific and public benefit, and highlight new and emerging areas that show particular promise. The developments that we describe thus span from fundamental scientific research, such as THz astronomy and the emergent area of THz quantum optics, to highly applied and commercially and societally impactful subjects that include 6G THz communications, medical imaging, and climate monitoring and prediction.

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Section: Advances In Science and Technology To Meet Challengesmentioning

confidence: 99%

The 2023 terahertz science and technology roadmap

Dhillon¹,

Vitiello²,

Linfield³

et al. 2023

J. Phys. D: Appl. Phys.

229

View full text Add to dashboard Cite

show abstract

“…In this detection model, the color, intensity, and direction of saliency mapping can be calculated by the difference between adjacent pixels and multiscale center. en, the final saliency map is obtained by combining the above three feature maps [10][11][12]. Figure 1 demonstrates the specific algorithm steps.…”

Section: Improved Generative Adversarialmentioning

confidence: 99%

Optimization of a Deep Learning Algorithm for Security Protection of Big Data from Video Images

Geng¹,

Yan

Lu³

2022

Computational Intelligence and Neuroscience

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With the rapid development of communication technology, digital technology has been widely used in all walks of life. Nevertheless, with the wide dissemination of digital information, there are many security problems. Aiming at preventing privacy disclosure and ensuring the safe storage and sharing of image and video data in the cloud platform, the present work proposes an encryption algorithm against neural cryptography based on deep learning. Primarily, the image saliency detection algorithm is used to identify the significant target of the video image. According to the significant target, the important region and nonimportant region are divided adaptively, and the encrypted two regions are reorganized to obtain the final encrypted image. Then, after demonstrating how attackers conduct attacks to the network under the ciphertext attack mode, an improved encryption algorithm based on selective ciphertext attack is proposed to improve the existing encryption algorithm of the neural network. Besides, a secure encryption algorithm is obtained through detailed analysis and comparison of the security ability of the algorithm. The experimental results show that Bob’s decryption error rate will decrease over time. The average classification error rate of Eve increases over time, but when Bob and Alice learn a secure encryption network structure, Eve’s classification accuracy is not superior to random prediction. Chosen ciphertext attack-advantageous neural cryptography (CCA-ANC) has an encryption time of 14s and an average speed of 69mb/s, which has obvious advantages over other encryption algorithms. The self-learning secure encryption algorithm proposed here significantly improves the security of the password and ensures data security in the video image.

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“…8. 150 In addition, efforts by Kitahara et al showed that FD THz OCT complements traditional TD OCT. Signal processing advances in the field allowed them to provide reliable tomographic measurements despite substantial noise levels in their broadband THz source. 151 In conclusion, the appropriate groundwork has been laid for efficient, robust, high-resolution THz OCT.…”

Section: Developments In Optical Coherence Tomographymentioning

confidence: 99%

Survey of terahertz photonics and biophotonics

et al. 2020

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We review the advances of terahertz (THz) science and technology in biophotonics, including related challenges and solutions. The main impediment to THz spectroscopy and imaging in this field is the high absorption of the THz beam in water. Hence, transmission imaging and spectroscopy of thick wet tissue using THz radiation has generally been quite difficult. However, the absorption of THz waves by water molecules is so strong that increasing the power of the THz source can lead to structural and functional changes in tissues, so solutions must go beyond a larger power output. In terms of resolution, THz imaging is superior to ultrasound but inferior to visible light microscopy. Owing to its unique material analysis capabilities, promising diagnosis applications have been demonstrated through THz imaging and spectroscopy. Unfortunately, many applications are limited by beam penetration depth and resolution. Hence, researchers from a wide variety of scientific and technical fields have been actively improving these features through the development of electronic devices and materials. In addition, groundbreaking optical architecture and materials to reduce beam absorption in the optics of a system and generate focused beams with smaller diameters have been proposed. On the software side, image processing techniques to computationally enhance the resolution and quality of THz imaging have been proposed. Data science and machine learning to automate the diagnosis of defects and diseases through processing THz images and spectroscopy data have been proposed. We have reviewed the applications of THz radiation in biophotonics and research achievements toward advancing these applications. A conclusion with a roadmap toward increasing the footprint of the THz technology in biophotonics is also proposed.

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Co-registered combined OCT and THz imaging to extract depth and refractive index of a tissue-equivalent test object

Cited by 17 publications

References 40 publications

The 2023 terahertz science and technology roadmap

The 2023 terahertz science and technology roadmap

Optimization of a Deep Learning Algorithm for Security Protection of Big Data from Video Images

Survey of terahertz photonics and biophotonics

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