309 research outputs found

    Dielectric modelling of human skin and breast tissue in terahertz frequencies : potential application to cancer detection

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    University of Technology Sydney. Faculty of Engineering and Information Technology.Growing developments in the generation and detection of terahertz (THz) radiation over more than two decades have created a strong incentive for researchers to study the biomedical applications of terahertz imaging. Contrasts in the THz images of various types of cancer, especially skin and breast cancer, are associated with changes in the dielectric properties of cancerous tissues. In fact, dielectric models can explain the interaction between terahertz radiation and human tissue at a molecular level just as their parameters have the potential for becoming indicators of cancer. However, dielectric modelling of various forms of human tissue remains limited due to a number of factors, especially suboptimal fitting algorithms and tissue heterogeneity. Thanks to the high water content of human skin, its dielectric response to terahertz radiation can be described by the double Debye model. The existing fitting method using a nonlinear least square algorithm can extract the model parameters which track their measurements accurately at frequencies higher than one THz but poorly at lower frequencies. However, the majority of dielectric contrast between normal and cancerous skin tissues has been observed in the low THz range. Accordingly, this research has developed two global optimization algorithms which are capable of globally accurate tracking thereby supporting the full validity of the double Debye model in simulating the dielectric spectra of human skin in the THz frequencies. Numerical results confirm their superiority over the conventional methods. Furthermore, the next goal of the study is to apply statistical analysis to the parameters of the double Debye model in order to test their discrimination capability of skin cancer from normal tissue. Linear programming and support vector machine algorithms have also been employed using these parameters to classify normal skin tissue and basal cell carcinoma. By combining the double Debye parameters, the classification accuracy has shown significant improvement. The encouraging outcomes confirm the classification potential of the double Debye parameters. The double Debye model, however, has been shown to be not suitable for simulating human breast tissue due to its low water content and heterogeneous structure, thus limiting the understanding of the THz dielectric response of breast tissue. To overcome this problem, this study proposes a new non-Debye dielectric model to fit the dielectric spectra of human breast tissue. Due to the mathematical complexity of the fitting procedure, a sampling gradient algorithm of non-smooth optimization is used to optimize the fitting solution. Simulation results confirm applicability of the non-Debye model through its exceptional ability to fit the examined data. Statistical measures have also been used to analyse the possibility of using the parameters of this model to differentiate breast tumours from healthy breast tissue. Based on the statistical analysis, popular classification methods such as support vector machines and Bayesian neural network have also been applied to examine these parameters and their combinations for breast cancer classification. The obtained classification accuracies indicate the classification potential of the model parameters as well as highlighting several valuable features of the parameter combinations

    High correlation of double Debye model parameters in skin cancer detection

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    © 2014 IEEE. The double Debye model can be used to capture the dielectric response of human skin in terahertz regime due to high water content in the tissue. The increased water proportion is widely considered as a biomarker of carcinogenesis, which gives rise of using this model in skin cancer detection. Therefore, the goal of this paper is to provide a specific analysis of the double Debye parameters in terms of non-melanoma skin cancer classification. Pearson correlation is applied to investigate the sensitivity of these parameters and their combinations to the variation in tumor percentage of skin samples. The most sensitive parameters are then assessed by using the receiver operating characteristic (ROC) plot to confirm their potential of classifying tumor from normal skin. Our positive outcomes support further steps to clinical application of terahertz imaging in skin cancer delineation

    Ocjena preciznog dielektičnog modela i izabranih patenta o otkrivanju raka dojke pomoću mikrovalova

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    Advances in microwave breast cancer detection and imaging during last decade are reported in this review paper. An introduction to breast cancer and detection methods and detailed information about microwave imaging and selected patents are presented. The advantages and disadvantages of the presented patents and also state of breast cancer detection and imaging are discussed. Microwave imaging for breast tumor detection is considered to be promising, as it is believed that there is a significant or detectable contrast in malignant, benign and normal tissues over a broad frequency range. Also, there have been many dielectric models, especially the double Debye model has been used to define the dielectric response of different biological tissues. On the other hand, double Debye model is not accurate for human breast tissue because there are knowledge limitations about the structure, dynamics, and macroscopic behavior of breast tissue. It is vital that, according to frequency, accurate dielectric model should be chosen in detection systems.Ovaj rad govori o naprecima u otkrivanju i snimanju raka dojke pomoću mikrovalova u posljednjem desetljeću. Dan je uvod o raku dojke i metodama otkrivanja te detaljne informacije o snimanju pomoću mikrovalova i izabranim patentima. Raspravljene su prednosti i nedostaci prezentiranih patenata kao i trenutno stanje u detektiranju i snimanju raka dojke. Snimanje mikrovalovima kako bi se otkrio rak dojke metoda je od koje se mnogo očekuje, pošto se smatra kako postoje znatni ili primjetni kontrasti između malignih, benignih i normalnih tkiva kroz široki raspon frekvencija. Također, postoje mnogi dielektrični modeli, posebno se dvostruki Debye model koristio u definiranju dielektričnog odziva raznih bioloških tkiva. S druge strane, dvostruki Debye model nije precizan prilikom korištenja za ljudska tkiva, jer postoje ograničenja u saznanjima oko strukture, dinamike i makroskopskog ponašanja tkiva dojke. Neophodno je, ovisno o frekvenciji, izabrati ispravan dielektrični model u sustavima za detekciju

    Metamaterial Biosensor on THz Regime for Early Detection and Quantitative Analysis of Skin Cancer

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    'Terahertz imaging exhibits significant potential in the early detection of skin cancer. This work introduces a metamaterial unit cell that operates in the terahertz (THz) band for non-invasive contact-based detection of skin cancer. The sensor relies solely on the reflection coefficient response, offering high sensitivity to subtle changes in tissue properties without complex signal processing, making it potentially cost-effective and simpler to implement for early cancer detection. The simulations utilised 3D models representing normal skin, basal cell carcinoma (BCC), and melanoma skin types. The dielectric characteristics of the samples were determined using the Double Debye model. The simulation demonstrated that the metamaterial design exhibited properties of a double negative material at the specific frequency of 1.15 THz. Following skin contact and malignancy, the reflectance coefficient exhibited a shift towards lower frequencies. The melanoma sample exhibited the most significant shift in resonance towards lower frequencies, indicating a more severe form of cancer compared to BCC. Furthermore, it was observed that the disparity in resonance frequencies between normal skin and malignant skin increased as the thickness of the sample increased. The sensor’s sensitivity in identifying cancer thickness was measured at 9.25 GHz/µm for basal cell carcinoma (BCC) and 10.2 GHz/µm for melanoma. In addition, the linear regression analysis demonstrated a strong correlation between the resonance frequency and the variation in cancer thickness, as indicated by the R2 values of 0.9948 and 0.9947 for BCC and melanoma, respectively. These findings demonstrate that the sensor can detect skin cancer of any severity at the initial stages of its development

    Terahertz Spectroscopy for Gastrointestinal Cancer Diagnosis

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    In this chapter, we present a number of sensitive measurement modalities for the study and analysis of human cancer-affected colon and gastric tissue using terahertz (THz) spectroscopy. Considerable advancements have been reached in characterization of bio-tissue with some accuracy, although too dawn, and still long and exhaustive work have to be done towards well-established and reliable applications. The advent of the THz-time-domain spectroscopy (THz-TDS) test modality at a sub-picosecond time resolution has arguably fostered an intensive work in this field’s research line. The chapter addresses some basic theoretical aspects of this measurement modality with the presentation of general experimental laboratory setup diagrams for THz generation and detection, sample preparation aspects, samples optical parameters calculation procedures and data analysis

    Spectroscopic methods for medical diagnosis at terahertz wavelengths

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    Terahertz (THz) radiation lies between the microwave and infrared regions of the electromagnetic spectrum. THz radiation excites intermolecular interactions and is non-ionising making it a viable tool for medical imaging. This thesis describes the development and validation of spectroscopic methods for diagnosis of tissue pathologies at THz wavelengths. Theoretical techniques were developed to determine the origin of the contrast seen in THz images of biological tissue. Specific biological tissues investigated in this thesis were colonic tissues with the aim of determining the origin of contrast between healthy and diseased tissue in THz images. This thesis investigates the interaction of THz radiation with matter using simple tissue phantoms made from five biologically relevant materials: water, methanol, lipid, sucrose and gelatin. Phantoms are designed to imitate the spectroscopic properties of tissue at specific wavelengths where physical properties of the phantom, such as concentration and homogeneity, can be accurately controlled. The frequency-dependent absorption coefficients, refractive indices and Debye relaxation times of the pure compounds were measured and used as prior knowledge in the different theoretical methods for the determination of concentration. Three concentration analysis methods were investigated, a) linear spectral decomposition, b) spectrally averaged dielectric coefficient method and c) the Debye relaxation coefficient method. These methods were validated on phantoms by determining the concentrations of the phantom chromophores and comparing to the known composition. Two-component phantoms were made comprising water with methanol, lipid, sucrose or gelatin. Two different three-component phantoms were created; one with water, methanol and sucrose and a second with water, gelatin and lipid. The accuracy and resolution of each method was determined to assess the potential of each method as a tool for medical diagnosis at THz wavelengths. Finally, the spectroscopic methods were applied to measurements of ex-vivo colon tissues containing cancerous and dysplastic regions. Statistical analysis of the reflected time-domain waveforms demonstrated good distinction between healthy and diseased tissues with an estimated sensitivity of 89.2% and specificity of 78.3%

    The 2017 Terahertz Science and Technology Roadmap

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    Science and technologies based on terahertz frequency electromagnetic radiation (100GHz-30THz) have developed rapidly over the last 30 years. For most of the 20th century, terahertz radiation, then referred to as sub-millimeter wave or far-infrared radiation, was mainly utilized by astronomers and some spectroscopists. Following the development of laser based terahertz time-domain spectroscopy in the 1980s and 1990s the field of THz science and technology expanded rapidly, to the extent that it now touches many areas from fundamental science to “real world” applications. For example THz radiation is being used to optimize materials for new solar cells, and may also be a key technology for the next generation of airport security scanners. While the field was emerging it was possible to keep track of all new developments, however now the field has grown so much that it is increasingly difficult to follow the diverse range of new discoveries and applications that are appearing. At this point in time, when the field of THz science and technology is moving from an emerging to a more established and interdisciplinary field, it is apt to present a roadmap to help identify the breadth and future directions of the field. The aim of this roadmap is to present a snapshot of the present state of THz science and technology in 2016, and provide an opinion on the challenges and opportunities that the future holds. To be able to achieve this aim, we have invited a group of international experts to write 17 sections that cover most of the key areas of THz Science and Technology. We hope that The 2016 Roadmap on THz Science and Technology will prove to be a useful resource by providing a wide ranging introduction to the capabilities of THz radiation for those outside or just entering the field as well as providing perspective and breadth for those who are well established. We also feel that this review should serve as a useful guide for government and funding agencies
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