Abstract-Reflection type scanning laser terahertz near-field spectroscopy and imaging system for bio-applications

Kosuke Okada, Kazunori Serita, Iwao Kawayama, Hironaru Murakami, and Masayoshi Tonouchi

https://www.osapublishing.org/abstract.cfm?URI=cleo_si-2018-SW3D.4

We developed a reflection type scanning laser THz near-field spectroscopy and imaging system and evaluated its basic performance. We found that this system has huge potential for high-resolution, high-sensitive and high-speed biological measurements.

© 2018 The Author(s)

Abstract-Automatic evaluation of traumatic brain injury based on terahertz imaging with machine learning

Jia Shi, Yuye Wang, Tunan Chen, Degang Xu, Hengli Zhao, Linyu Chen, Chao Yan, Longhuang Tang, Yixin He, Hua Feng, and Jianquan Yao

https://www.osapublishing.org/oe/abstract.cfm?uri=oe-26-5-6371

The imaging diagnosis and prognostication of different degrees of traumatic brain injury (TBI) is very important for early care and clinical treatment. Especially, the exact recognition of mild TBI is the bottleneck for current label-free imaging technologies in neurosurgery. Here, we report an automatic evaluation method for TBI recognition with terahertz (THz) continuous-wave (CW) transmission imaging based on machine learning (ML). We propose a new feature extraction method for biological THz images combined with the transmittance distribution features in spatial domain and statistical distribution features in normalized gray histogram. Based on the extracted feature database, ML algorithms are performed for the classification of different degrees of TBI by feature selection and parameter optimization. The highest classification accuracy is up to 87.5%. The area under the curve (AUC) scores of the receiver operating characteristics (ROC) curve are all higher than 0.9, which shows this evaluation method has a good generalization ability. Furthermore, the excellent performance of the proposed system in the recognition of mild TBI is analyzed by different methodological parameters and diagnostic criteria. The system can be extensible to various diseases and will be a powerful tool in automatic biomedical diagnostics.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Abstract-Composite multiscale entropy analysis of reflective terahertz signals for biological tissues

Rui Zhang, Yuezhi He, Kai Liu, Liangliang Zhang, Shijing Zhang, Emma Pickwell-MacPherson, Yuejin Zhao, and Cunlin Zhang

https://www.osapublishing.org/oe/abstract.cfm?uri=oe-25-20-23669

We demonstrate a composite multiscale entropy (CMSE) method of terahertz (THz) signal complexity analysis to distinguish different biological tissues. The THz signals reflected from fresh porcine skin and muscle tissues were measured and analyzed. The statistically significant difference and separation of the two tissues based on several parameters were analyzed and compared for THz spectroscopy and imaging, which verified the better performance of the CMSE method and further enhancement of the contrast among THz signals that interact with different tissues. This process provides a better analysis and discrimination method for THz spectroscopy and imaging in biomedical applications.

© 2017 Optical Society of America

Abstract-Observation of dehydration dynamics in biological tissues with terahertz digital holography

Lihan Guo, Xinke Wang, Peng Han, Wenfeng Sun, Shengfei Feng, Jiasheng Ye, and Yan Zhang

https://www.osapublishing.org/ao/abstract.cfm?uri=ao-56-13-F173

A terahertz (THz) digital holographic imaging system is utilized to investigate natural dehydration processes in three types of biological tissues, including cattle, mutton, and pork. An image reconstruction algorithm is applied to remove the diffraction influence of THz waves and further improve clarity of THz images. From THz images of different biological specimens, distinctive water content as well as dehydration features of adipose and muscle tissues are precisely distinguished. By analyzing THz absorption spectra of these samples, temporal evolution characteristics of the absorbances for adipose and muscle tissues are described and compared in detail. Discrepancies between water retention ability of different animal tissues are also discussed. The imaging technique provides a valuable measurement platform for biological sensing.

© 2017 Optical Society of America

Abstract-Fast design of broadband terahertz diffusion metasurfaces

Jie Zhao, Qiang Cheng, Tian Qi Wang, Wei Yuan, and Tie Jun Cui

https://www.osapublishing.org/oe/abstract.cfm?uri=oe-25-2-1050

A method for fast design of broadband terahertz diffusion metasurface is presented. The proposed metasurface is composed by three kinds of simply patterned elements with different resonant properties. To obtain the best broadband performance with the lowest backward reflections, a genetic algorithm is developed to manipulate the resonances for the fast determination of element geometries. An inverse discrete Fourier transform method is used to predict the scattering pattern of the metasurface with high accuracy and low time consumption, significantly enhancing the efficiency of the array-pattern design. The proposed fast design flow will benefit a broad range of terahertz applications, such as biological detection and imaging.

© 2017 Optical Society of America

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