Time frequency analysis in terahertz pulsed imaging

Recent advances in laser and electro-optical technologies have made the previously under-utilized terahertz frequency band of the electromagnetic spectrum accessible for practical imaging. Applications are emerging, notably in the biomedical domain. In this chapter the technique of terahertz pulsed imaging is introduced in some detail. The need for special computer vision methods, which arises from the use of pulses of radiation and the acquisition of a time series at each pixel, is described. The nature of the data is a challenge since we are interested not only in the frequency composition of the pulses, but also how these differ for different parts of the pulse. Conventional and short-time Fourier transforms and wavelets were used in preliminary experiments on the analysis of terahertz pulsed imaging data. Measurements of refractive index and absorption coefficient were compared, wavelet compression assessed and image classification by multidimensional clustering techniques demonstrated. It is shown that the timefrequency methods perform as well as conventional analysis for determining material properties. Wavelet compression gave results that were robust through compressions that used only 20% of the wavelet coefficients. It is concluded that the time-frequency methods hold great promise for optimizing the extraction of the spectroscopic information contained in each terahertz pulse, for the analysis of more complex signals comprising multiple pulses or from recently introduced acquisition techniques

Shedding New Light on Cancer with Non-Linear Optical Microscopy

Oesophageal cancer, one of the most aggressive cancer types is considered the seventh most common cancer in terms of incidence and the sixth most common cause of cancer deaths worldwide due to late diagnosis. In the UK, the oesophageal cancer incidence rate has increased by approximately 10% since the 1990s. At present, histopathology is the gold standard method for the diagnosis of oesophageal cancer, which rely on biopsy collection using an endoscopy procedure followed by the histological sample’s preparation. This method is invasive, time-consuming, and largely based on the pathologist's experience of diagnosis. Therefore, new diagnostic techniques are required to provide non-invasive methods for early and rapid diagnosis. Raman scattering has the potential to replace histopathology as the gold standard for diagnosis for a wide range of diseases. Raman scattering provides stain-free imaging with chemical-specificity derived from the intrinsic vibrational signatures of biomolecules. However, the low scattering cross-section severely limits the image acquisition speeds and like conventional histopathology, requires tissue sectioning to provide morphological imaging below the surface of tissue biopsies. Stimulated Raman scattering (SRS) has recently appeared as a powerful technique for (near)real-time Raman imaging in intact tissue samples. Thework in this thesis aimed to develop the stimulated Raman scattering (SRS) for rapid wavelength tuning and chemical imaging of clinical samples, such as cancer biopsies. This was achieved by making modification to a laser cavity to reduce the time of the wavelength tuning by approximately 35 times compared to the original cavity design. Furthermore, the cavity modification led to the spectra being separated efficiently and the wavelength tuning controlled by cavity length changes only. The improved design was applied to image frozen oesophageal tissues, which have four major pathology groups, normal, inflammation, columnar-lined (Barrett's) oesophagus (CLO) and low-grade dysplasia. A large area imaging was performed using the SRS technique at 2930 cm-1 for four different oesophageal tissues, which presented the morphological and structural information. However, histopathological diagnosis depends on the visualisation of the cell nucleus in the tissue. This component was not highlighted until the stimulated Raman histology approach was developed for small regions of interest in the CLO and the low-grade dysplasia sample, which required two different frequencies at 2840 cm-1 and 2930 cm-1. All SRS images were compared to haematoxlin and eosin (H&E) stained sections. Further comparisons were made between SRS and Raman imaging techniques, with SRS offering faster acquisition times and a higher spatial resolution. The spectral signature for the different pathological groups in the oesophageal tissues were explored in the high wavenumber (2800 – 2930 cm-1) region using hyperspectral SRS and compared with the spectra from the Raman. K-means clustering analysis was used to explore the morphochemical information using the CLO and low-grade dysplasia sections. Both techniques were able to demonstrate unique information such as the epithelial cells that form the oesophagus glands and surrounding connective tissue. It is concluded that SRS has the power to be one of the ideal imaging modalities to gather the molecular information in biological samples. However, it still needs more development due to the complexity of the system

Microscopy with undetected photons in the mid-infrared

Owing to its capacity for unique (bio)-chemical specificity, microscopy withmid-IR illumination holds tremendous promise for a wide range of biomedical and industrial applications. The primary limitation, however, remains detection; with current mid-IR detection technology often marrying inferior technical capabilities with prohibitive costs. This has lead to approaches that shift detection towavelengths into the visible regime, where vastly superior silicon-based cameratechnology is available. Here, we experimentally show how nonlinear interferometry with entangled light can provide a powerful tool for mid-IR microscopy, while only requiring near-infrared detection with a standard CMOS camera. In this proof-of-principle implementation, we demonstrate intensity imaging overa broad wavelength range covering 3.4-4.3um and demonstrate a spatial resolution of 35um for images containing 650 resolved elements. Moreover, we demonstrate our technique is fit for purpose, acquiring microscopic images of biological tissue samples in the mid-IR. These results open a new perspective for potential relevance of quantum imaging techniques in the life sciences.Comment: back-to-back submission with arXiv:2002.05956, Anna V. Paterova, Sivakumar M. Maniam, Hongzhi Yang, Gianluca Grenci, and Leonid A. Krivitsky, "Hyperspectral Infrared Microscopy With Visible Light

Three-color Coherent Anti-Stokes Raman Scattering: from tracing dynamics of elementary excitations in solids to imaging of live cells.

Commonly used laser based spectroscopy and imaging techniques have both advantages and disadvantages. Therefore, a system that allows access to molecularly specific properties is highly desired. The primary objective of the study is to demonstrate state-of-the art for coherent laser spectroscopy and microscopy and their applications in biomedical imaging and condensed matter characterization. This study also demonstrates the capabilities and application of timedomain coherent spectroscopy technique to characterize soft- (aqueous media, large organic molecules and biological media) and traditional condensed matter (including solid state crystals, inorganic microstructures and photonic materials). Work on coherent multi-photon microscopy and approaches concerned to the experimental realization of femtosecond time domain ‘Coherent Anti-Stokes Raman Scattering Spectroscopy’ (CARS) are demonstrated. Problems and issues related to generation of broadly tunable femtosecond optical parametric oscillators (OPOs) based on periodically poled lithium Tantalate crystal, Experimental realization of human blood sample, tracing phonon dynamics and elementary excitations in KTP crystal and its decay time are presente

Automatic refocus and feature extraction of single-look complex SAR signatures of vessels

In recent years, spaceborne synthetic aperture radar ( SAR) technology has been considered as a complement to cooperative vessel surveillance systems thanks to its imaging capabilities. In this paper, a processing chain is presented to explore the potential of using basic stripmap single-look complex ( SLC) SAR images of vessels for the automatic extraction of their dimensions and heading. Local autofocus is applied to the vessels' SAR signatures to compensate blurring artefacts in the azimuth direction, improving both their image quality and their estimated dimensions. For the heading, the orientation ambiguities of the vessels' SAR signatures are solved using the direction of their ground-range velocity from the analysis of their Doppler spectra. Preliminary results are provided using five images of vessels from SLC RADARSAT-2 stripmap images. These results have shown good agreement with their respective ground-truth data from Automatic Identification System ( AIS) records at the time of the acquisitions.Postprint (published version