Optical Coherence Tomography and Its Non-medical Applications

Optical coherence tomography (OCT) is a promising non-invasive non-contact 3D imaging technique that can be used to evaluate and inspect material surfaces, multilayer polymer films, fiber coils, and coatings. OCT can be used for the examination of cultural heritage objects and 3D imaging of microstructures. With subsurface 3D fingerprint imaging capability, OCT could be a valuable tool for enhancing security in biometric applications. OCT can also be used for the evaluation of fastener flushness for improving aerodynamic performance of high-speed aircraft. More and more OCT non-medical applications are emerging. In this book, we present some recent advancements in OCT technology and non-medical applications

Multi-beam miniaturized volumetric scanning microscopy with a single 1-dimensional actuation

Miniaturized optical imaging systems often use a 2-dimensional (2-D) actuator such as a piezoelectric tube or microelectromechanical system actuator for the acquisition of 2-D and higher dimensional images over an areal field of view (FOV). Piezoelectric tubes are the most compact, but usually produce impractical sub-millimetre FOVs and are difficult to fabricate at scale, leading to high costs. Planar piezoelectric bending actuators ('benders') are substantially lower cost and capable of much larger actuations, albeit 1-dimensional (1-D) and traditionally inadequate for 2-D steering tasks. We present a piezoelectric bender imaging system that exploits mechanical motion coupling to produce multi-millimetre scale 2-D scan coverage. Leveraging optical coherence tomography with a long coherence length laser, we further extend the FOV using three depth-multiplexed imaging beams from optical fibres resonating in synchronicity across the width of the bender. Each fibre had a FOV of ~2.1 x 1.5 mm, contributing to a stitched field of ~2.1 x 2.9 mm with a beam resolution of 12.6 um full-width at half-maximum. Imaging of biological samples including stomach tissue, an ant and cell spheroids was performed. This multi-fold improvement in imaging coverage and cost-effectiveness promises to accelerate the advent of piezoelectric scanning in compact devices such as endoscopes for biomedicine, and headsets for augmented/virtual reality and neuroscience

Internal fingerprint extraction

Fingerprints are a non-invasive biometric that possess significant advantages. However, they are subject to surface erosion and damage; distortion upon scanning; and are vulnerable to fingerprint spoofing. The internal fingerprint exists as the undulations of the papillary junction - an intermediary layer of skin - and provides a solution to these disadvantages. Optical coherence tomography is used to capture the internal fingerprint. A depth profile of the papillary junction throughout the OCT scans is first constructed using fuzzy c-means clustering and a fine-tuning procedure. This information is then used to define localised regions over which to average pixels for the resultant internal fingerprint. When compared to a ground-truth internal fingerprint zone, the internal fingerprint zone detected automatically is within the measured bounds of human error. With a mean- squared-error of 21.3 and structural similarity of 96.4%, the internal fingerprint zone was successfully found and described. The extracted fingerprints exceed their surface counterparts with respect to orientation certainty and NFIQ scores (both of which are respected fingerprint quality assessment criteria). Internal to surface fingerprint correspondence and internal fingerprint cross correspondence were also measured. A larger scanned region is shown to be advantageous as internal fingerprints extracted from these scans have good surface correspondence (75% had at least one true match with a surface counterpart). It is also evidenced that internal fingerprints can constitute a fingerprint database. 96% of the internal fingerprints extracted had at least one corresponding match with another internal fingerprint. When compared to surface fingerprints cropped to match the internal fingerprints’ representative area and locality, the internal fingerprints outperformed these cropped surface counterparts. The internal fingerprint is an attractive biometric solution. This research develops a novel approach to extracting the internal fingerprint and is an asset to the further development of technologies surrounding fingerprint extraction from OCT scans. No earlier work has extracted or tested the internal fingerprint to the degree that this research has

Optical Methods in Sensing and Imaging for Medical and Biological Applications

The recent advances in optical sources and detectors have opened up new opportunities for sensing and imaging techniques which can be successfully used in biomedical and healthcare applications. This book, entitled ‘Optical Methods in Sensing and Imaging for Medical and Biological Applications’, focuses on various aspects of the research and development related to these areas. The book will be a valuable source of information presenting the recent advances in optical methods and novel techniques, as well as their applications in the fields of biomedicine and healthcare, to anyone interested in this subject

Multi-Frame Superresolution Optical Coherence Tomography for High Lateral Resolution 3D Imaging

We report that high lateral resolution and high image quality optical coherence tomography (OCT) imaging can be achieved by the multi-frame superresolution technique. With serial sets of slightly lateral shifted low resolution C-scans, our multi-frame superresolution processing of these special sets at each depth layer can reconstruct a higher resolution and quality lateral image. Layer by layer repeat processing yields an overall high lateral resolution and quality 3D image. In theory, the superresolution with a subsequent deconvolution processing could break the diffraction limit as well as suppress the background noise. In experiment, about three times lateral resolution improvement has been verified from 24.8 to 7.81 μm and from 7.81 to 2.19 μm with the sample arm optics of 0.015 and 0.05 numerical apertures, respectively, as well as the image quality doubling in dB unit. The improved lateral resolution for 3D imaging of microstructures has been observed. We also demonstrated that the improved lateral resolution and image quality could further help various machine vision algorithms sensitive to resolution and noise. In combination with our previous work, an ultra-wide field-of-view and high resolution OCT has been implemented for static non-medical applications. For in vivo 3D OCT imaging, high quality 3D subsurface live fingerprint images have been obtained within a short scan time, showing beautiful and clear distribution of eccrine sweat glands and internal fingerprint layer, overcoming traditional 2D fingerprint reader and benefiting important biometric security applications

Matching Fingerprints with a Toroidal Iterative Closest Point Algorithm

We develop a generalisable Cartesian-toroidal Iterative Closest Points (ICP) fingerprint matcher. Both 2D and 3D minutiae are cast as point clouds that we augment with additional features. Iterative Closest Points (ICP) is immediately applicable to these data structures, yet nonetheless relatively unexplored in the fingerprinting domain. We apply our ICP-based method to conventional 2D minutiae and 3D features extracted from Optical Coherence Tomography (OCT) scans of fingertips. We show that ICP is a viable strategy to fingerprint matching using the diverse features in the internal fingerprint skin. Using 3D minutiae alone gave an Area Under the Curve (AUC) of 0.961, and 3D minutiae augmented with mean local OCT intensity gave an AUC of 0.973. Regarding 2D minutiae, our method offers a significant improvement over the baseline NIST Bozorth3 algorithm: an AUC of 0.94 versus 0.86 on an artificial dataset generated with SFinGe. In addition, ICP incurs only nominal computation cost when additional features are added