Continuous-Wave THz Imaging for Biomedical Samples

Terahertz (THz) is an electromagnetic spectrum with a frequency range from 0.1 to 10 THz, which is located in between the microwave and infrared regions. The unique features of THz waves make them eligible for use in various medical applications. The THz imaging is one of them, which is mainly based on the analysis and processing of the transmission and reflection spectrum information of the sample. This chapter mainly presents the research status and prospects of several THz medical imaging systems and their applications for medical imaging in biological tissues. As the demand for technology grows, high-performance THz imaging systems are becoming indispensable. The ability of the THz time-domain spectroscopy (THz-TDS) system to extract spectra from amplitude and phase information opens virtually unlimited possibilities for imaging applications. The performance achievements of THz-TDS-based imaging with potential research on its fast-imaging components for solving the existing limitations of imaging speed are also presented. Furthermore, the latest developments of several THz-TDS-based imaging methods, including tomography imaging and near-field imaging, are highlighted with their performance improvement. Additionally, the rapid development of THz-TDS as a highly versatile analytical tool for the characterisation of pharmaceutical materials has drawn considerable attention. One of the greatest biomedical potentials of THz imaging is the use of molecular spectroscopy for diagnostics, which is exponentially advanced and moving closer to progress. It is now evident that different types of biomolecules leave distinctive spectral fingerprints in the THz region, which considerably widens the coverage of its technology application including in-vitro and in-vivo measurements of small molecules of clinical importance in point of care and diagnostic systems. In-vivo molecular imaging is considered the next frontier in medical diagnostics, which would be ideally performed non-invasively. Recent achievements in the field of medical imaging have dramatically enhanced the early detection and treatment of many pathological conditions. THz imaging systems can help in detecting early cancer before it is visible or sensitive to any other identification resources. The THz images can distinguish between healthy tissue and basal cell carcinoma and therefore help in mapping the exact margins of early-stage tumours. By obtaining both frequency and time-domain information, the THz imaging can ensure enhanced detection of cancer and provide sharper imaging and molecular fingerprinting. THz biomedical imaging has become a modality of interest due to its ability to simultaneously acquire both image and spectral information. Advanced digital image processing algorithms are greatly needed to assist in screening, diagnosis and treatment. Finally, we summarise the obstacles in the way of the application of THz biomedical imaging application technology in clinical detection, which need to be investigated and overcome in the future.

The detection of concealed suspicious objects in public places is a critical issue and a popular research topic. Terahertz (THz) imaging technology, as an emerging detection method, can penetrate materials without emitting ionizing radiation, providing a new approach to detecting concealed suspicious objects. This study focuses on the detection of concealed suspicious objects wrapped in different materials such as polyethylene and kraft paper, including items like scissors, pistols, and blades, using THz imaging technology. To address issues such as the lack of texture details in THz images and the contour similarity of different objects, which can lead to missed detections and false alarms, we propose a THz concealed suspicious object detection model based on SMR–YOLO (SPD_Mobile + RFB + YOLO). This model, based on the MobileNext network, introduces the spatial-to-depth convolution (SPD-Conv) module to replace the backbone network, reducing computational and parameter load. The inclusion of the receptive field block (RFB) module, which uses a multi-branch structure of dilated convolutions, enhances the network’s depth features. Using the EIOU loss function to assess the accuracy of predicted box localization further optimizes convergence speed and localization accuracy. Experimental results show that the improved model achieved mAP@0.5 and mAP@0.5:0.95 scores of 98.9% and 89.4%, respectively, representing improvements of 0.2% and 1.8% over the baseline model. Additionally, the detection speed reached 108.7 FPS, an improvement of 23.2 FPS over the baseline model. The model effectively identifies concealed suspicious objects within packages, offering a novel approach for detection in public places.

Owing to the unique characteristics of terahertz (THz) waves and their interaction with matter, THz imaging has significant potential in diverse fields, including life sciences, non-destructive quality control, and security. However, today’s THz technology faces major obstacles in providing the cost, compactness, and functional scope that is required to facilitate a wide-reaching use outside the laboratory. Therefore, the general aim of this thesis is to increase the societal impact of THz technology by exploring novel THz imaging modalities with integrated circuits (ICs) based on conventional silicon technolgy. Previous research in THz ICs mostly focused on building compact integrated source and detector components for far-field imaging systems that exploit the ability of THz waves to penetrate through diverse dielectric materials. One part of this thesis joins this research and demonstrates low-cost volumetric THz imaging based on computed tomography with silicon components for the first time. To this end, a high-power 0.43 THz source in 0.13 μm silicon-germanium heterojunction bipolar transistor (SiGe HBT) technology is developed in this thesis. However, the resolution of THz far-field imaging is limited by diffraction to the millimeter range, whereas some of the most promising THz applications in life sciences, such as intraoperative imaging of cancerous tissue, are in need for a microscopic resolution to resolve material properties on the cellular level. This thesis presents the realization of microscopic THz imaging with a silicon-based sensor system. The central contribution of this work is the development and analysis of a 128-pixel THz near-field sensor System-on-a-Chip (SoC) operating at 0.55 THz and showing a spatial resolution around 10 μm. The sensor exploits the capacitive near-field interaction between split-ring-resonator probes and imaging objects, giving an imaging contrast based on the dielectric permittivity. To simultaneously enable real-time image acquisition, high sensor sensitivity, and an integration level that is comparable to conventional consumer electronics, the full integration capabilities of a high-speed 0.13 μm SiGe bipolar CMOS (SiGe-BiCMOS) technology are exploited. In particular, the presented SoC employs cointegration of a chip-scale one-dimensional THz sensor front-end, analog signal processing, and digital circuitry for controlling the chip and external communication. The achieved results in terms of imaging speed, system cost, and integration level reach well beyond the state of the art in THz near-field imaging. The ability to rapidly acquire THz images with micrometer-scale resolution will be of benefit to fundamental research into material properties in the THz range and lays the foundation for the exploration of THz bioimaging applications on the cellular level. In particular, the sensor enables the conduction of large-scale clinical studies on the relevance of microscopic THz imaging to ex vivo tumor margin assessment in breast cancer surgeries for the first time.

Terahertz (THz) hydration sensing and image has been a topic of increased interest recently due largely to improvements in source and detector technology and the identification of applications where current hydration sensing techniques are insufficient. THz medical imaging is an expanding field of research and tissue hydration plays a key role in the contrast observed in THz tissue reflectance and absorbance maps. This paper outlines the most recent results in burn and corneal imaging where hydration maps were used to assess tissue status. A 3 day study was carried out in rat models where a THz imaging system was used to assess the severity and extent of burn throughout the first day of injury and at the 24, 48, and 72 hour time points. Marked difference in tissue reflectance were observed between the partial and full thickness burns and image features were identified that may be used as diagnostic markers for burn severity. Companion histological analysis performed on tissue excised on Day 3 confirms hypothesized burn severity. The results of these preliminary animal trials suggest that THz imaging may be useful in burn wound assessment where current clinical modalities have resolution and/or sensitivity insufficient for accurate diagnostics.

Over the past decade, INO has leveraged its expertise in the development of uncooled microbolometer detectors for infrared imaging to produce terahertz (THz) imaging systems. By modifying its microbolometer-based focal plane arrays to enhance absorption in the THz bands and by developing custom THz imaging lenses, INO has developed a leading-edge THz imaging system, the IRXCAM-THz-384 camera, capable of exploring novel applications in the emerging field of terahertz imaging and sensing. Using appropriate THz sources, results show that the IRXCAM-THz-384 camera is able to image a variety of concealed objects of interest for applications such as non-destructive testing and weapons detections. By using a longer wavelength (94 GHz) source, it is also capable of sensing the signatures of various objects hidden behind a drywall panel. This article, written as a review of THz research at INO over the past decade, describes the technical components that form the IRXCAM-THz-384 camera and the experimental setup used for active THz imaging. Image results for concealed weapons detection experiments, an exploration of wavelength choice on image quality, and the detection of hidden objects behind drywall are also presented.

Simple SummaryIn order to realize rapid and complete pre-screening in the pathological examination of gastric cancer and assist in quickly determining the boundary between cancerous and healthy cells, we developed a fast-scanning near-field terahertz (THz) imaging system. This imaging system is compact, low-cost, and easy to operate. THz examination does not need any processing after sectioning, and the diagnostic results are directly displayed in images within one minute. Compared with the H&E staining method, THz imaging diagnosis uses a quantitative absorption coefficient to distinguish cancer tissue and healthy tissue, which makes the automation of the tissue sampling pre-screening procedure possible and will save valuable time to help quickly define cancer tissue. At the same time, the spatial resolution of our near-field imaging system reaches λ/17. Using THz imaging to accurately define the margins of cancer can not only conserve healthy tissues but also minimize the number of second surgical procedures, which would save a lot of additional hospital resources.The distinguishable absorption contrast among healthy gastric tissues, carcinoma in situ and cancer tissues in the THz frequency range is one of the keys to realizing gastric cancer diagnosis by THz imaging. Based on microwave devices and a sub-wavelength fiber, we developed a fast-scanning THz imaging system combined with the principle of surface plasmon resonance enhancement. This imaging system has a near-field λ/17 spatial resolution and imaging S/N ratio as high as 108:1, and the image results are directly displayed within 1 min. We also successfully demonstrated the image diagnostic capability on sliced tissues from eight patients with gastric cancer. The results indicate that THz absorption images can not only clearly distinguish cancer tissue from healthy tissues but also accurately define the margins of cancer. Through a medical statistical study of 40 sliced tissues from 40 patients, we prove that THz imaging can be used as a standalone method to diagnose gastric cancer tissues with a diagnostic specificity and sensitivity of 100%. Compared with the H&E staining method, THz imaging diagnosis makes the automation of tissue-sampling pre-screening procedure possible and assists in quickly determining the boundary between cancerous and healthy tissues.

Molecular spectroscopy has been widely used to identify pesticides. The main limitation of this approach is the difficulty of identifying pesticides with similar molecular structures. When these pesticide residues are in trace and mixed states in plants, it poses great challenges for practical identification. This study proposed a state-of-the-art method for the rapid identification of trace (10 mg·L−1) and multiple similar benzimidazole pesticide residues on the surface of Toona sinensis leaves, mainly including benzoyl (BNL), carbendazim (BCM), thiabendazole (TBZ), and their mixtures. The new method combines high-throughput terahertz (THz) imaging technology with a deep learning framework. To further improve the model reliability beyond the THz fingerprint peaks (BNL: 0.70, 1.07, 2.20 THz; BCM: 1.16, 1.35, 2.32 THz; TBZ: 0.92, 1.24, 1.66, 1.95, 2.58 THz), we extracted the absorption spectra in frequencies of 0.2–2.2 THz from images as the input to the deep convolution neural network (DCNN). Compared with fuzzy Sammon clustering and four back-propagation neural network (BPNN) models (TrainCGB, TrainCGF, TrainCGP, and TrainRP), DCNN achieved the highest prediction accuracies of 100%, 94.51%, 96.26%, 94.64%, 98.81%, 94.90%, 96.17%, and 96.99% for the control check group, BNL, BCM, TBZ, BNL + BCM, BNL + TBZ, BCM + TBZ, and BNL + BCM + TBZ, respectively. Taking advantage of THz imaging and DCNN, the image visualization of pesticide distribution and residue types on leaves was realized simultaneously. The results demonstrated that THz imaging and deep learning can be potentially adopted for rapid-sensing detection of trace multi-residues on leaf surfaces, which is of great significance for agriculture and food safety.

We propose real-time two-dimensional (2D) terahertz (THz) tomography for 2D crosssectional imaging of moving objects. The proposed method does not require mechanical scanning elements for time delay and sample position, which are essential for conventional THz tomography. For this purpose, a 2D spatiotemporal THz image is acquired at a frame rate of 10frame/s by a combination of electro-optical time-to-space conversion and line focusing of a THz beam on a sample. We demonstrate the use of real-time 2D THz tomography for real-time monitoring of the paint thickness in a moving paint sample and the drying progress in a wet paint film. The proposed method provides a powerful tool for non-ionizing and non-contact probing in the fields of nondestructive testing and biomedical diagnostics.

Terahertz (THz) imaging is increasingly used in the cultural heritage field. In particular, continuous wave (CW) and low frequency THz is attracting more attention. The first application of the THz technique inherent to the cultural heritage field dates back 10 years ago. Since 2006, tangible improvements have been conducted in the refinement of the technique, with the aim to produce clear maps useful for any art restorer. In this paper, a CW THz (0.1 THz) imaging system was used to inspect paintings on canvas both in reflection and in transmission modes. In particular, two paintings were analyzed: in the first one, similar materials and painting execution of the original artwork were used, while in the second one, the canvas layer is slightly different. Flash thermography was used herein together with the THz method in order to observe the differences in results for the textile support materials. A possible application of this method for the detection of artwork forgery requires some parameterization and analysis of various materials or thickness influence which will be addressed in a future study. In this work, advanced image processing techniques including principal component thermography (PCT) and partial least squares thermography (PLST) were used to process the infrared data. Finally, a comparison of CW THz and thermographic results was conducted.

This paper presents an image morphing algorithm for quantitative evaluation methodology of terahertz (THz) images of excised breast cancer tumors. Most current studies on the assessment of THz imaging rely on qualitative evaluation, and there is no established benchmark or procedure to quantify the THz imaging performance. The proposed morphing algorithm provides a tool to quantitatively align the THz image with the histopathology image. Freshly excised xenograft murine breast cancer tumors are imaged using the pulsed THz imaging and spectroscopy system in the reflection mode. Upon fixing the tumor tissue in formalin and embedding in paraffin, an FFPE tissue block is produced. A thin slice of the block is prepared for the pathology image while another THz reflection image is produced directly from the block. We developed an algorithm of mesh morphing using homography mapping of the histopathology image to adjust the alignment, shape, and resolution to match the external contour of the tissue in the THz image. Unlike conventional image morphing algorithms that rely on internal features of the source and target images, only the external contour of the tissue is used to avoid bias. Unsupervised Bayesian learning algorithm is applied to THz images to classify the tissue regions of cancer, fat, and muscles present in xenograft breast tumors. The results demonstrate that the proposed mesh morphing algorithm can provide more effective and accurate evaluation of THz imaging compared with existing algorithms. The results also showed that while THz images of FFPE tissue are highly in agreement with pathology images, challenges remain in assessing THz imaging of fresh tissue.

Focal Plane Array (FPA) detector has characteristics of low cost, operating at room temperature, compatibility with the silicon CMOS technology, and high detecting performance, therefore it becomes a hot spot in infrared (IR) or terahertz (THz) detect field recently. However, the tradition structure of micro-bolometer has the conflict of the pixel size and thermal performance. In order to improve the detecting performance of small pixel size bolometer, high fill factor and low thermal conductance design should be considered. In IR detecting, double layers structure is an efficient method to improve the absorption of micro-bolometer and reduce thermal conductance. The three-dimension model of small size micro-bolometer was built in this article. The thermal and mechanical characters of those models were simulated and optimized, and finally the double layer structure micro-bolometer was fabricated with multifarious semiconductor recipes on the readout integrated chip wafer. For THz detecting, to improve the detecting performance, different dimension THz detectors based on micro-bridge structure were designed and fabricated to get optimizing micro-bolometer parameters from the test results of membrane deformation. A nanostructured titanium thin film absorber is integrated in the micro-bridge structure of the VOx micro-bolometer to enhance the absorption of THz radiation. Continuous-wave THz detection and imaging are demonstrated with a 2.52 THz far infrared CO2 laser and fabricated 320×240 vanadium oxide micro-bolometer focal plane array with optimized cell structure. With this detecting system, THz imaging of metal concealed in wiping cloth and envelope is demonstrated.

The method of election-pass filtering and image fusion based on the wavelet transform is presented for eliminating the fringes in the continuous wave (CW) Terahertz (THz) Images. The CW THz images have the appearance of sinusoidal waves covering the image with standing wave patterns. The patterns result from reflected inside of the imaging system interfering with the images coming from the sample. The pattern interferes with contrast enhancement techniques, and can make the analysis of small areas difficult. An analysis is taken on the traditional method dealing with this problem by Frequency Domain Filtering and notch filtering, and the disadvantages of the traditional methods are shown. The Wavelet Transform is chosen to deal with the THz images and eliminate interference fringes. In the method, when the size of object is larger than one interference fringe, the character of the object can also be reserved. And the image fusion based on the Wavelet Transform is used to combine the background and the target with pixel-level fusion, which is proposed to improve the speed of identification and the quality of the fused image. Comparing the image restored via wavelet transform with other images, it can be found that the scope of continuous wave THz imaging's application can be extended and clearer images can be acquired.

Focused THz wave from a spintronic terahertz Fresnel Zone Plate emitter

Terahertz (THz) imaging technology has a great potential application owing to the unique properties of THz wave that has both permeability and feature of straight [1]. Especially for real-time THz imaging detectors, field-effect transistor (FET)-based plasmonic THz detectors [2] are now being intensively developed in multi-pixel array configuration by exploiting the silicon (Si) CMOS technology advantages of low-cost and high integration density. In terms of the circuit design approach, by utilizing resistive self-mixing in the FET channel, a 0.65 THz focal plane array (FPA) detector was reported [3] and more recently, a 1 k-pixel camera has been demonstrated for a real-time THz imaging by 65-nm CMOS technology [4]. In this work, we experimentally demonstrate the real-time terahertz (THz) imaging of moving object on the conveyer belt by implementing asymmetric FET-based plasmonic 2×200 array scanner in 65-nm CMOS technology. Based on the enhanced detecting performance from our previous works [5][6], fast and uniform detection results are presented by novel device and circuit design for real-time THz imaging.

Imaging of biological tissues with terahertz microscopy based on a cross-filament