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Optical Coherence Tomography (OCT) emerged as a technology for the detection of retinal disease. Owing to its excellent performance and ability to provide in-vivo high-resolution images, the popularity increased dramatically across various application domains. Consequently, OCT has been widely used in other branches of medical applications, i.e., oncology and otolaryngology, industry, and agriculture. Despite its widespread use, OCT image analysis is an inherently subjective, laborious, and time-intensive task that requires expertise. Deep Learning (DL) stands as the current state-of-the-art method for image analysis. Hence, several research groups have directed their efforts toward incorporating DL algorithms with OCT imaging to reduce the time as well as the subjectivity. This article comprehensively reviews the principal technological advancements in DL methods applied across various OCT applications. Additionally, it explores the latest trends in developing DL methods for OCT, highlights their limitations, and discusses future opportunities in a comprehensive manner.

Clinical fetal monitoring devices can only be operated by medical professionals and are overly costly, prone to detrimental false positives, and emit radiation. Thus, highly accurate, easily accessible, simplified, and cost-effective fetal monitoring devices have gained an enormous interest in obstetrics. In this study, a cost-effective and user-friendly wearable home fetal movement and distress detection device is developed and assessed for early-stage design progression by facilitating continuous, comfortable, and non-invasive monitoring of the fetus during the final trimester. The functionality of the developed prototype is mainly based on a microcontroller, a single accelerometer, and a specialized fetal phonocardiography (fPCG) acquisition board with a low-cost microphone. The developed system is capable of identifying fetal movement and monitors fetal heart rhythm owing to its considerable sensitivity. Further, the device includes a Global System for Mobile Communication (GSM)-based alert system for instant distress notifications to the mother, proxy, and emergency services. By incorporating digital signal processing, the system achieves zero false negatives in detecting fetal movements, which was validated against an open-source database. The acquired results clearly substantiated the efficacy of the fPCG acquisition board and alarm system, ensuring the prompt identification of fetal distress.

Circular leaf spot (CLS) disease poses a significant threat to persimmon cultivation, leading to substantial harvest reductions. Existing visual and destructive inspection methods suffer from subjectivity, limited accuracy, and considerable time consumption. This study presents an automated pre-identification method of the disease through a deep learning (DL) based pipeline integrated with optical coherence tomography (OCT), thereby addressing the highlighted issues with the existing methods. The investigation yielded promising outcomes by employing transfer learning with pre-trained DL models, specifically DenseNet-121 and VGG-16. The DenseNet-121 model excels in differentiating among three stages of CLS disease (healthy (H), apparently healthy (or healthy-infected (HI)), and infected (I)). The model achieved precision values of 0.7823 for class-H, 0.9005 for class-HI, and 0.7027 for class-I, supported by recall values of 0.8953 for class-HI and 0.8387 for class-I. Moreover, the performance of CLS detection was enhanced by a supplemental quality inspection model utilizing VGG-16, which attained an accuracy of 98.99% in discriminating between low-detail and high-detail images. Moreover, this study employed a combination of LAMP and A-scan for the dataset labeling process, significantly enhancing the accuracy of the models. Overall, this study underscores the potential of DL techniques integrated with OCT to enhance disease identification processes in agricultural settings, particularly in persimmon cultivation, by offering efficient and objective pre-identification of CLS and enabling early intervention and management strategies.

Speckle patterns are a generic feature in coherent imaging techniques like optical coherence tomography (OCT). Although speckles are granular like noise texture, which degrades the image, they carry information that can be benefited by processing and thereby furnishing crucial information of sample structures, which can serve to provide significant important structural details of samples in in vivo longitudinal pre-clinical monitoring and assessments. Since the motions of tissue molecules are indicated through speckle patterns, speckle variance OCT (SV-OCT) can be well-utilized for quantitative assessments of speckle variance (SV) in biological tissues. SV-OCT has been acknowledged as a promising method for mapping microvasculature in transverse-directional blood vessels with high resolution in micrometers in both the transverse and depth directions. The fundamental scope of this article reviews the state-of-the-art and clinical benefits of SV-OCT to assess biological tissues for pre-clinical applications. In particular, focus on precise quantifications of in vivo vascular response, therapy assessments, and real-time temporal vascular effects of SV-OCT are primarily emphasized. Finally, SV-OCT-incorporating pre-clinical techniques with high potential are presented for future biomedical applications.

Measurement(s) Apple and persimmon leaf layer thickness Technology Type(s) Optical coherence tomography imaging and MATLAB programs

Characterizing plant material is crucial in terms of early disease detection, pest control, physiological assessments, and growth monitoring, which are essential parameters to increase production in agriculture and prevent unnecessary economic losses. The conventional methods employed to assess the aforementioned parameters have several limitations, such as invasive inspection, complexity, high time consumption, and costly features. In recent years, optical coherence tomography (OCT), which is an ultra-high resolution, non-invasive, and real-time unique image-based approach has been widely utilized as a significant and potential tool for assessing plant materials in numerous aspects. The obtained OCT cross-sections and volumetrics, as well as the amplitude signals of plant materials, have the capability to reveal vital information in both axial and lateral directions owing to the high resolution of the imaging system. This review discusses recent technological trends and advanced applications of OCT, which have been potentially adapted for numerous agricultural applications, such as non-invasive disease screening, optical signals-based growth speed detection, the structural analysis of plant materials, and microbiological discoveries. Therefore, this review offers a comprehensive exploration of recent advanced OCT technological approaches for agricultural applications, which provides insights into their potential to incorporate OCT technology into numerous industries.

Bio-mechatronics is an interdisciplinary scientific field that emphasizes the integration of biology and mechatronics to discover innovative solutions for numerous biomedical applications. The broad application spectrum of bio-mechatronics consists of minimally invasive surgeries, rehabilitation, development of prosthetics, and soft wearables to find engineering solutions for the human body. Fiber-optic-based sensors have recently become an indispensable part of bio-mechatronics systems, which are essential for position detection and control, monitoring measurements, compliance control, and various feedback applications. As a result, significant advancements have been introduced for designing and developing fiber-optic-based sensors in the past decade. This review discusses recent technological advancements in fiber-optical sensors, which have been potentially adapted for numerous bio-mechatronic applications. It also encompasses fundamental principles, different types of fiber-optical sensors based on recent development strategies, and characterizations of fiber Bragg gratings, optical fiber force myography, polymer optical fibers, optical tactile sensors, and Fabry–Perot interferometric applications. Hence, robust knowledge can be obtained regarding the technological enhancements in fiber-optical sensors for bio-mechatronics-based interdisciplinary developments. Therefore, this review offers a comprehensive exploration of recent technological advances in fiber-optical sensors for bio-mechatronics. It provides insights into their potential to revolutionize biomedical and bio-mechatronics applications, ultimately contributing to improved patient outcomes and healthcare innovation.

Abstract Nail beautification is a widely applied gender independent practice. Excessive nail beautifications and nail-arts have a direct impact on the nail structure and can cause nail disorders. Therefore, the assessment of post-progressive nail-art effects on the nail is essential to maintain optimal nail health and to avoid any undesirable disorders. In this study, in vivo nails were examined in control stage, with a nail-art stage, and after removing the nail-art stage using a 1310 nm spectral-domain optical coherence tomography (SD-OCT) system. The acquired cross-sectional OCT images were analyzed by a laboratory customized signal processing algorithm to obtain scattered intensity profiling assessments that could reveal the effects of nail beautification on the nail plate. The formation and progression of cracks on the nail plate surface were detected as an effect of nail beautification after 72 h of nail-art removal. Changes in backscattered light intensity and nail plate thickness of control and art-removed nails were quantitatively compared. The results revealed the potential feasibility of the developed OCT-based inspection procedure to diagnose post-progressive nail-art effects on in vivo nail plate, which can be helpful to prevent nail plate damages during art removal through real-time monitoring of the boundary between the nail plate and nail-art. Besides nail-art effects, the developed method can also be used for the investigation of nail plate abnormalities by examining the inconsistency of internal and external nail plate structure, which can be diagnosed with both qualitative and quantitative assessments from a clinical perspective.

The accurate screening of otitis media (OM) lies in clarifying the numerous confounding and quantitative factors that are discovered during primary inspections. Increased awareness about bacterial biofilms and inflammation has allowed researchers to develop a better understanding of the bacterial infections that occur in the middle ear. In this study, four live guinea pigs were inoculated with Streptococcus pneumonia to induce OM-related inflammatory changes. Since optical techniques have been effectively used for diagnosis in medicine, low-coherence interferometry-based optical coherence tomography (OCT) was employed for depth-resolved high-resolution data screening. Multiple locations of the tympanic membrane (TM), mastoid mucosa, and round window membrane were examined to assess inflammatory changes. We performed qualitative assessments and thickness quantifications and investigated the variations due to adverse inflammatory affects. The findings of the present study provide a better understanding of S. pneumonia bacteria caused inflammatory changes in middle ear and it further provides a fundamental platform for future clinical utility.

Optical fiber is widely used in optical coherence tomography (OCT) to propagate light precisely with low attenuation and low dispersion. However, the total optical path length within the optical fiber varies in accordance with changes of the temperature. This leads changes in the total optical travel path of the interfering signals and results in shifting of OCT image position to an unintended depth pixel value. In this paper, we presented the temperature-based automatic path length compensating method in OCT to limit the external temperature effect and control the image position in micro-scale without manual movement of optical components. By utilizing developed hardware and software of automatic temperature control system, the external temperature of optical fiber is precisely regulated that evokes thermal expansion and finally changes the physical length of fiber, which is main mechanism of temperature-based path length compensating method. The effectiveness of the presented method was verified by two-dimensional OCT images of mirror and in vivo retina. The obtained results confirmed the path length variance due to temperature change is computable and can be regulated in real-time for whole pixel range of OCT image. Therefore, the proposed temperature-based path length compensating method can be used as an alternative method to precisely control the position of OCT image, while eliminating the effect of external temperature and apply to effectively configuring compact optical systems.

Large-scale product inspection is an important aspect in thin film industry to identify defects with a high precision. Although vision line scan camera (VLSC)-based inspection has been frequently implemented, it is limited to surface inspections. Therefore, to overcome the conventional drawbacks, there is a need to extend inspection capabilities to internal structures. Considering that VLSC systems have access to rich information, such as color and texture, high-resolution real-time multimodal optical synchronization between VLSC and dual spectral domain optical coherence tomography (SD-OCT) systems was developed with a laboratory customized in-built automated defect-tracking algorithm for optical thin films (OTFs). Distinguishable differences in the color and texture of the bezel area were precisely determined by the VLSC. Detailed OCT assessments were conducted to verify the detection of previously unobtainable border regions and micrometer-range sub-surface defects. To enhance the accuracy of the method, VLSC images were aided for the precise surface defect identification using OCT and the image acquisition, signal processing, image analysis, and classification of both techniques were simultaneously processed in real-time for industrial applicability. The results demonstrate that the proposed method is capable of detecting and enumerating total number of defects in OTF samples with exceptional resolution and in a cost-effective manner facilitating wide area inspection for OTF samples.

Dental crowns are used to restore decayed or chipped teeth, where their surfaces play a key role in this restoration process, as they affect the fitting and stable bonding of the prostheses. The surface texture of crowns can interfere with this restoration process, therefore the measurement of their inner surface roughness is very important but difficult to achieve using conventional imaging methods. In this study, the inner surfaces of dental crowns were three-dimensionally (3D) visualized using swept-source optical coherence tomography (SS-OCT) system. Nine crowns were fabricated with a commercial 3D printer using three different hatching methods (one-way, cross, and 30° angle counter-clockwise) and three different build direction angles (0°, 45°, and 90°). In addition, an image processing algorithm was developed, which uses morphological filtering, boundary detection, and a high-pass frequency filtering technique, to quantitatively evaluate the inner surface roughness of the dental crowns cross-sections with the depth-of-focus set to match two different regions. The averaged smoothness of fabricated crown was effectively produced using the cross-hatching and the build direction angle of 90° by the respective process. Thus, the results confirm the potential use of this methodology to determine the best parameters to use in 3D fabrication for improving the effectiveness and stability of dental prostheses.

The rapid evolution towards industrial automation has widened the usage of industrial applications, such as robot arm manipulation and bin picking. The performance of these applications relies on object detection and pose estimation through visual data. In fact, the clarity of those data significantly influences the accuracy of object detection and pose estimation. However, a majority of visual data corresponding to metal or glossy surfaces tend to have specular reflections that reduce the accuracy. Hence, this work aims to improve the performance of industrial bin-picking tasks by reducing the effects of specular reflections. This work proposes a deep learning (DL)-based neural network model named SpecToPoseNet to improve object detection and pose estimation accuracy by intelligently removing specular reflections. The proposed work implements a synthetic data generator to train and test the SpecToPoseNet. The conceptual breakthrough of this work is its ability to remove specular reflections from scenarios with multiple objects. With the use of the proposed method, we could reduce the fail rate of object detection to 7%, which is much less compared to specular images (27%), U-Net (20%), and the basic SpecToPoseNet model (11%). Thus, it is claimable that the performance improvements gained are positive influences of the proposed DL-based contexts such as bin-picking.

Pores are the microscopic openings in the skin that emit oils and sweat. Pores can appear larger due to acne, sun damage, or increased sebum production, a waxy and oily substance that causes oily skin. Investigating and extracting sebum from facial pores is essential for treating skin issues as the enlargement of the pores causes higher susceptibility of the skin to microbe aggressions and inflammatory reactions. In this study, we assessed the volumetric size of pores before and after the sebum extraction using spectral domain optical coherence tomography (SD-OCT). To properly estimate the volume of the sebum before and after extraction, multiple cross-sectional OCT images were selected. The area of a single pixel was calculated from the OCT images using the scanning range. Furthermore, an algorithm was developed to use the pixel area to calculate the full volumetric size of the skin pore. This research illustrates the use of a high-resolution microscopic analysis using SD-OCT in dermatological research and can operate as a guideline for future research investigations in evaluating non-destructively wounded tissue analysis, underlying skin biochemistry, and facial statistical approaches in skin parameters for moisturizer treatment.

In the past decade, there has been an increase in the development of sensitive, high-resolution, non-invasive diagnostic methods for periodontic diseases. Optical coherence tomography (OCT) has attracted considerable attention in clinical settings. In this paper, a reliable, robust algorithm for the detection of gingival sulcus in 2D OCT cross-sectional images is proposed. Previously, the measurement of gingival sulcus in OCT images has been performed by manual identification using two-dimensional (2D) cross-sectional images. The automated detection of gingival sulcus continuity in 2D OCT images may help medical practitioners to assess important features of gingival tissues. The Sobel and canny operators have mainly been used for boundary and edge detection in OCT images. However, these algorithms are highly sensitive to noise and speckle in OCT images. To overcome these limitations, we propose an algorithm for the quantitative depth measurement of the human gingival sulcus, based on averaged intensity difference. In this paper, we utilized two commercially-available swept-source OCT systems operating at center wavelengths of 1310 and 1060 nm to image gingival sulcus of human samples in vivo. The images were processed using three algorithms: canny, Sobel, and averaged intensity difference.

On-field in situ inspection of Marssonina coronaria infected apple blotch for apple leaf specimens was demonstrated using compact backpack-type optical coherence tomography (OCT). Simultaneously, the acquired OCT results were precisely matched with a widely used agricultural plant pathogen inspection technique called loop-mediated isothermal amplification (LAMP) to confirm on-field applicability of the compact backpack-type OCT. Specimens were examined for 8 weeks. Automated Amplitude-scan (A-scan) depth profiling and post-processed infected tissue boundary detection from acquired OCT images were performed to investigate the increase in the internal layer gaps of the leaf specimens resulting from the disease. Clearly identifiable morphological difference between healthy and infected-suspected specimens was observed through the OCT images, which were well correlated with LAMP results. OCT-LAMP correlations and confirmed feasibility study results conclude that the compact backpack-type OCT diagnosing modality can be effective and extensively applicable for various novel agricultural discoveries.

An internal and marginal fit between prosthesis and abutment is an important factor of the durability of dental prosthesis. In this paper, we have proposed the use of swept-source optical coherence tomography (OCT) as a novel application for non-ionized and high-resolution measurements of internal and marginal discrepancies at anatomically critical four points, such as occlusal, angle, axial, and margin during prosthesis attachment. A tooth model was fabricated by a 3D printing technique, and the dental prosthesis was designed using dental CAD software. The cross-sectional images along with intensity peak profile analysis of the sample were acquired using the OCT system for measurements of fit. The demonstrated qualitative and quantitative evaluations can be well-utilized for assessment of the internal and marginal fit of dental prosthesis.

Abstract The tremendous advances achieved in the biophotonics technologies have intensified the necessity for non-invasive modalities that can characterize diverse biological materials with increased sensitivity and resolution. Optical coherence tomography (OCT) is one of the techniques that has been applied for biological applications in medicine and agriculture to identify structural properties. Herein, we report the successful incorporation of OCT for the identification of morphological changes that occur as a result of the bitter rot disease, through continuous detection of structural changes. Detailed inner morphological structural changes occurring in fruit specimens were precisely analyzed as a function of the disease incubation period using OCT. The conducted histological correlation and quantitative three-dimensional evaluations provide a robust platform for further discoveries related to plant materials. The results highlight the initial identification of bitter rot progression on apple specimens owing to the non-invasive inspection capability of OCT. Therefore, we expect that the proposed method will enable immediate sensitivity improvements in the inspection of plant diseases for postharvest utility.

Laser transmission welding offers significant benefits over conventional welding techniques enabling single-stage rapid plastic joining. The quality of laser transmission welded products is commonly assessed by measuring the weld penetration depth, hardened weld boundary, and inspecting the formation of porosity. However, the existing methods of verification are inevitably accompanied by destruction of the specimen. Thus, non-destructive quality assessment methods for laser transmission welding have gained attention recently. Here, we demonstrated an extended industrial application of 860 nm wavelength-based spectral domain optical coherence tomography for the non-destructive inspection of the aforementioned quality parameters of laser transmission welded industrial plastic materials, i.e., polycarbonate and acrylonitrile butadiene styrene copolymer. The acquired cross-sectional resolution and volumetric and intensity profiles sufficiently contributed to the quality assessment procedure, revealing the weld boundary and porosity formation, and thus confirming the potential applicability of optical coherence tomography for the quality inspection of laser transmission welded products.

Mice and rats are rodent specimens commonly used in multidisciplinary research. Specifically, vasculature imaging of rodents has been widely performed in preclinical studies using various techniques, such as computed tomography, magnetic resonance imaging, and ultrasound imaging. Photoacoustic CT (PACT) is a noninvasive, nonionizing optical imaging technique derived from photoacoustic tomography and benefits from using intrinsic endogenous contrast agents to produce three-dimensional volumetric data from images. In this study, a commercial PACT device was employed to assess the cervicothoracic vasculature of mouse and rat specimens, which has rarely been examined using PACT, under two conditions with depilation and skin incision. Various blood vessels, including the common carotid artery, internal/external jugular veins, cranial vena cava, internal thoracic vein, and mammary, were identified in the acquired PACT images. The difference between the depilated and skin-incised specimens also revealed the presence of branches from certain blood vessels and specific anatomical features such as the manubrium of the sternum. This study presents detailed PACT images observing the cervicothoracic vasculature of rodent specimens and is expected to be used as a reference for various preclinical experiments on mice and rats.

The aim of this study was to quantitatively assess the residual adhesive on orthodontic ceramic bracket-removed dental surface. In orthodontic process, ceramic bracket was repeated debonding physically, then the adhesive remained on the dental surface. The residual adhesive caused a lack of adhesive strength between dental and ceramic bracket. Since commonly used adhesive in orthodontics is translucent, residual adhesive is hard to be detected with conventional microscopes. Therefore, 1310 nm center wavelength swept-source OCT system based on laboratory customized image processing algorithm was used for the precise detection of residual adhesive on tooth surface. The algorithm separates residual adhesive from dental surface by comparing the height of adjacent B-scan images, while providing color-scaled images emphasizing the thickness information of residual adhesive. Finally, the acquired results were compared with microscopic and adhesive remnant index scoring gold standards, while the comparison confirmed the potential merits and the improvements of the proposed method over gold standards.

Whole-directional scanning methodology is required to observe distinctive features of an entire physical structure with a three dimensional (3D) visualization. However, the implementation of whole-directional scanning is challenging for conventional optical coherence tomography (OCT), which scans a limited portion of the sample by utilizing unidirectional and bidirectional scanning methods. Therefore, in this paper an integrated quad-scanner (QS) strategy-based OCT method was implemented to obtain the whole-directional volumetry of a sample by employing four scanning arms installed around the sample. The simultaneous and sequential image acquisition capabilities are the conceptual key points of the proposed QS-OCT method, and were implemented using four precisely aligned scanning arms and applied in a complementary way according to the experimental criteria. To assess the feasibility of obtaining whole-directional morphological structures, a roll of Scotch tape, an ex vivo mouse heart, and kidney specimens were imaged and independently obtained tissue images at different directions were delicately merged to compose the 3D volume data set. The results revealed the potential merits of QS-OCT-based whole-directional imaging, which can be a favorable inspection method for various discoveries that require the dynamic coordinates of the whole physical structure.

Survivors of either a hemorrhagic or ischemic stroke tend to acquire aphasia and experience spontaneous recovery during the first six months. Nevertheless, a considerable number of patients sustain aphasia and require speech and language therapy to overcome the difficulties. As a preliminary study, this article aims to distinguish aphasia caused from a temporoparietal lesion. Typically, temporal and parietal lesions cause Wernicke’s aphasia and Anomic aphasia. Differential diagnosis between Anomic and Wernicke’s has become controversial and subjective due to the close resemblance of Wernicke’s to Anomic aphasia when recovering. Hence, this article proposes a clinical diagnosis system that incorporates normal coupling between the acoustic frequencies of speech signals and the language ability of temporoparietal aphasias to delineate classification boundary lines. The proposed inspection system is a hybrid scheme consisting of automated components, such as confrontation naming, repetition, and a manual component, such as comprehension. The study was conducted involving 30 participants clinically diagnosed with temporoparietal aphasias after a stroke and 30 participants who had experienced a stroke without aphasia. The plausibility of accurate classification of Wernicke’s and Anomic aphasia was confirmed using the distinctive acoustic frequency profiles of selected controls. Accuracy of the proposed system and algorithm was confirmed by comparing the obtained diagnosis with the conventional manual diagnosis. Though this preliminary work distinguishes between Anomic and Wernicke’s aphasia, we can claim that the developed algorithm-based inspection model could be a worthwhile solution towards objective classification of other aphasia types.

Depth-visualizing sensitivity can be degraded due to imperfect optical alignment and non-equidistant distribution of optical signals in the pixel array, which requires a measurement of the re-sampling process. To enhance this depth-visualizing sensitivity, reference and sample arm-channeled spectra corresponding to different depths using mirrors were obtained to calibrate the spectrum sampling prior to Fourier transformation. During the process, eight interferogram patterns corresponding to point spread function (PSF) signals at eight optical path length differences were acquired. To calibrate the spectrum, generated intensity points of the original interferogram were re-indexed towards a maximum intensity range, and these interferogram re-indexing points were employed to generate a new lookup table. The entire software-based process consists of eight consecutive steps. Experimental results revealed that the proposed method can achieve images with a high depth-visualizing sensitivity. Furthermore, the results validate the proposed method as a rapidly performable spectral calibration technique, and the real-time images acquired using our technique confirm the simplicity and applicability of the method to existing optical coherence tomography (OCT) systems. The sensitivity roll-off prior to the spectral calibration was measured as 28 dB and it was halved after the calibration process.

Development of a dual-display handheld optical coherence tomography (OCT) system for retina and optic-nerve-head diagnosis beyond the volunteer motion constraints is reported. The developed system is portable and easily movable, containing the compact portable OCT system that includes the handheld probe and computer. Eye posterior chambers were diagnosed using the handheld probe, and the probe could be fixed to the bench-top cradle depending on the volunteers’ physical condition. The images obtained using this handheld probe were displayed in real time on the computer monitor and on a small secondary built-in monitor; the displayed images were saved using the handheld probe’s built-in button. Large-scale signal-processing procedures such as k-domain linearization, fast Fourier transform (FFT), and log-scaling signal processing can be rapidly applied using graphics-processing-unit (GPU) accelerated processing rather than central-processing-unit (CPU) processing. The Labview-based system resolution is 1,024 × 512 pixels, and the frame rate is 56 frames/s, useful for real-time display. The 3D images of the posterior chambers including the retina, optic-nerve head, blood vessels, and optic nerve were composed using real-time displayed images with 500 × 500 × 500 pixel resolution. A handheld and bench-top hybrid mode with a dual-display handheld OCT was developed to overcome the drawbacks of the conventional method.

Non-invasive investigation of rice leaf specimens to characterize the morphological formation and particular structural information that is beneficial for agricultural perspective was demonstrated using a low coherence interferometric method called swept source optical coherence tomography (SS-OCT). The acquired results non-invasively revealed morphological properties of rice leaf, such as bulliform cells; aerenchyma, parenchyma, and collenchyma layer; and vascular bundle. Beside aforementioned morphologic characteristics, several leaf characteristics associated with cytological mechanisms of leaf rolling (leaf inclination) were examined for the pre-identification of inevitable necrosis and atrophy of leaf tissues by evaluating acute angle information, such as angular characteristics of the external bi-directional angles between the lower epidermis layer and lower mid-vein, and internal angle of lower mid-vein. To further assist the pre-identification, acquired cross-sections were employed to enumerate the small veins of each leaf specimen. Since mutants enlarge leaf angles due to increased cell division in the adaxial epidermis, healthy and abnormal leaf specimens were morphologically and quantitatively compared. Therefore, the results of the method can be used in agriculture, and SS-OCT shows potential as a rigorous investigation method for selecting mutant infected rice leaf specimens rapidly and non-destructively compared to destructive and time consuming gold-standard methods with a lack of precision.

We have demonstrated the application of optical coherence tomography (OCT) in diagnosis of growth and spread of the gray leaf spot disease in Capsicum annuum leaf caused by the fungus Stemphylium lycopersici. Using 2D cross-sectional and 3D volumetric images of OCT, in vivo study of layer differences between fungus infected leaves and healthy leaves was observed with distinctive features. We observed that the internal layers of the disease-affected parts of the leaf seem to merge forming a single thick layer. The obtained OCT results verify the noninvasive diagnosis ability of fungal growth and spread in Capsicum annuum leaves and the applicability of this methodology for other plant diseases.

The non-destructive classification of plant materials using optical inspection techniques has been gaining much recent attention in the field of agriculture research. Among them, a near-infrared (NIR) imaging method called optical coherence tomography (OCT) has become a well-known agricultural inspection tool since the last decade. Here we investigated the non-destructive identification capability of OCT to classify diversely stained (with various staining agents) Capsicum annuum seed specimens of different cultivars. A swept source (SS-OCT) system with a spectral band of 1310 nm was used to image unstained control C. annuum seeds along with diversely stained Capsicum seeds, belonging to different cultivar varieties, such as C. annuum cv. PR Ppareum, C. annuum cv. PR Yeol, and C. annuum cv. Asia Jeombo. The obtained cross-sectional images were further analyzed for the changes in the intensity of back-scattered light (resulting due to dye pigment material and internal morphological variations) using a depth scan profiling technique to identify the difference among each seed category. The graphically acquired depth scan profiling results revealed that the control specimens exhibit less back-scattered light intensity in depth scan profiles when compared to the stained seed specimens. Furthermore, a significant back-scattered light intensity difference among each different cultivar group can be identified as well. Thus, the potential capability of OCT based depth scan profiling technique for non-destructive classification of diversely stained C. annum seed specimens of different cultivars can be sufficiently confirmed through the proposed scheme. Hence, when compared to conventional seed sorting techniques, OCT can offer multipurpose advantages by performing sorting of seeds in respective to the dye staining and provides internal structural images non-destructively.

We demonstrate that optical coherence tomography (OCT) is a plausible optical tool for in vivo detection of plant seeds and its morphological changes during growth. To investigate the direct impact of salt stress on seed germination, the experiment was conducted using Capsicum annuum seeds that were treated with different molar concentrations of NaCl. To determine the optimal concentration for the seed growth, the seeds were monitored for nine consecutive days. In vivo two-dimensional OCT images of the treated seeds were obtained and compared with the images of seeds that were grown using sterile distilled water. The obtained results confirm the feasibility of using OCT for the proposed application. Normalized depth profile analysis was utilized to support the conclusions.

The study of mosquitoes and analysis of their behavior are of crucial importance in the on-going efforts to control the alarming increase in mosquito-borne diseases. Furthermore, a non-destructive and real-time imaging technique to study the anatomical features of mosquito specimens can greatly aid the study of mosquitoes. In this study, we demonstrate the three-dimensional imaging capabilities of optical coherence tomography (OCT) for structural analysis of Anopheles sinensis mosquitoes. The anatomical features of An. sinensis head, thorax, and abdominal regions, along with the morphology of internal structures, such as foregut, midgut, and hindgut, were studied using OCT imaging. Two-dimensional and three-dimensional OCT images, used in conjunction with histological images, proved useful for anatomical analysis of mosquito specimens. By presenting this work as an initial study, we demonstrate the applicability of OCT for future mosquito-related entomological research, and also in identifying changes in mosquito anatomical structure.

The initial detection of dental caries is an essential biomedical requirement to barricade the progression of caries and tooth demineralization. The objective of this study is to introduce an optical frequency-domain imaging technique based quantitative evaluation method to calculate the volume and thickness of enamel residual, and a quantification method was developed to evaluate the total intensity fluctuation in depth direction owing to carious lesions, which can be favorable to identify the progression of dental caries in advance. The cross-sectional images of the ex vivo tooth samples were acquired using 1.3 μm spectral domain optical coherence tomography system (SD-OCT). Moreover, the advantages of the proposed method over the conventional dental inspection methods were compared to highlight the potential capability of OCT. As a consequence, the threshold parameters obtained through the developed method can be used as an efficient investigating technique for the initial detection of demineralization.

An application of spectral domain optical coherence tomography (SD-OCT) was demonstrated for a fast industrial inspection of an optical thin film panel. An optical thin film sample similar to a liquid crystal display (LCD) panel was examined. Two identical SD-OCT systems were utilized for parallel scanning of a complete sample in half time. Dual OCT inspection heads were utilized for transverse (fast) scanning, while a stable linear motorized translational stage was used for lateral (slow) scanning. The cross-sectional and volumetric images of an optical thin film sample were acquired to detect the defects in glass and other layers that are difficult to observe using visual inspection methods. The rapid inspection enabled by this setup led to the early detection of product defects on the manufacturing line, resulting in a significant improvement in the quality assurance of industrial products.

The feasibility of using the bio-photonic imaging technique to assess symptoms of circular leaf spot (CLS) disease in Diospyros kaki (persimmon) leaf samples was investigated. Leaf samples were selected from persimmon plantations and were categorized into three groups: healthy leaf samples, infected leaf samples, and healthy-looking leaf samples from infected trees. Visually non-identifiable reduction of the palisade parenchyma cell layer thickness is the main initial symptom, which occurs at the initial stage of the disease. Therefore, we established a non-destructive bio-photonic inspection method using a 1310 nm swept source optical coherence tomography (SS-OCT) system. These results confirm that this method is able to identify morphological differences between healthy leaves from infected trees and leaves from healthy and infected trees. In addition, this method has the potential to generate significant cost savings and good control of CLS disease in persimmon fields.