Optical Coherence Tomography Technology and Quality Improvement Methods for Optical Coherence Tomography Images of Skin: A Short Review

High-frequency photoacoustic and ultrasound imaging for skin evaluation: Pilot study for the assessment of a chemical burn

Skin architecture and its underlying vascular structure could be used to assess the health status of skin. A non-invasive, high resolution and deep imaging modality able to visualize skin subcutaneous layers and vasculature structures could be useful for determining and characterizing skin disease and trauma. In this study, a multispectral high-frequency, linear array-based photoacoustic/ultrasound (PAUS) probe is developed and implemented for the imaging of rat skin in vivo. The study seeks to demonstrate the probe capabilities for visualizing the skin and its underlying structures, and for monitoring changes in skin structure and composition during a 5-day course of a chemical burn. We analayze composition of lipids, water, oxy-hemoglobin, and deoxy-hemoglobin (for determination of oxygen saturation) in the skin tissue. The study successfully demonstrated the high-frequency PAUS imaging probe was able to provide 3D images of the rat skin architecture, underlying vasculature structures, and oxygen saturation, water, lipids and total hemoglobin.

Using optical coherence tomography to optimize Mohs micrographic surgery

Mohs micrographic surgery (MMS) is considered the gold standard for treating high-risk cutaneous basal cell carcinoma (BCC), but is expensive, time-consuming, and can be unpredictable as to how many stages will be required or how large the final lesion and corresponding surgical defect will be. This study is meant to investigate whether optical coherence tomography (OCT), a highly researched modality in dermatology, can be used preoperatively to map out the borders of BCC, resulting in fewer stages of MMS or a smaller final defect. In this prospective study, 22 patients with BCC undergoing surgical excision were enrolled at a single institution. All patients had previously received a diagnostic biopsy providing confirmation of BCC and had been referred to our center for excision with MMS. Immediately prior to performing MMS, OCT was used to map the borders of the lesion. MMS then proceeded according to standard protocol. OCT images were compared to histopathology for agreement. Histopathologic analysis of 7 of 22 MMS specimens (32%) revealed a total absence of BCC, indicating resolution of BCC after previous diagnostic biopsy. This outcome was correctly predicted by OCT imaging in 6 of 7 cases (86%). Nine tumors (9/22, 41%) had true BCC and required a single MMS stage, which was successfully predicted by pre-operative OCT analysis in 7 of 9 cases (78%). The final six tumors (27%) had true BCC and required two MMS stages for complete excision; preoperative OCT successfully predicted the need for a second stage in five cases (5/6, 83.3%). Overall, OCT diagnosed BCC with 95.5% accuracy (Cohen's kappa, κ = 0.89 (p-value =  < 0.01) in the center of the lesion. Following a diagnostic biopsy, OCT can be used to verify the existence or absence of residual basal cell carcinoma. When residual tumor is present that requires excision with MMS, OCT can be used to predict tumor borders, optimize surgery and minimize the need for additional surgical stages.

Photonics-powered augmented reality skin electronics for proactive healthcare: multifaceted opportunities

Rapid technological advancements have created opportunities for new solutions in various industries, including healthcare. One exciting new direction in this field of innovation is the combination of skin-based technologies and augmented reality (AR). These dermatological devices allow for the continuous and non-invasive measurement of vital signs and biomarkers, enabling the real-time diagnosis of anomalies, which have applications in telemedicine, oncology, dermatology, and early diagnostics. Despite its many potential benefits, there is a substantial information vacuum regarding using flexible photonics in conjunction with augmented reality for medical purposes. This review explores the current state of dermal augmented reality and flexible optics in skin-conforming sensing platforms by examining the obstacles faced thus far, including technical hurdles, demanding clinical validation standards, and problems with user acceptance. Our main areas of interest are skills, chiroptical properties, and health platform applications, such as optogenetic pixels, spectroscopic imagers, and optical biosensors. My skin-enhanced spherical dichroism and powerful spherically polarized light enable thorough physical inspection with these augmented reality devices: diabetic tracking, skin cancer diagnosis, and cardiovascular illness: preventative medicine, namely blood pressure screening. We demonstrate how to accomplish early prevention using case studies and emergency detection. Finally, it addresses real-world obstacles that hinder fully realizing these materials' extraordinary potential in advancing proactive and preventative personalized medicine, including technical constraints, clinical validation gaps, and barriers to widespread adoption.

Rapid measurement of epidermal thickness in OCT images of skin

Epidermal thickness (ET) changes are associated with several skin diseases. To measure ET, segmentation of optical coherence tomography (OCT) images is essential; manual segmentation is very time-consuming and requires training and some understanding of how to interpret OCT images. Fast results are important in order to analyze ET over different regions of skin in rapid succession to complete a clinical examination and enable the physician to discuss results with the patient in real time. The well-known CNN-graph search (CNN-GS) methodology delivers highly accurate results, but at a high computational cost. Our objective was to build a computational core, based on CNN-GS, able to accurately segment OCT skin images in real time. We accomplished this by fine-tuning the hyperparameters, testing a range of speed-up algorithms including pruning and quantization, designing a novel pixel-skipping process, and implementing the final product with efficient use of core and threads on a multicore central processing unit (CPU). We name this product CNN-GS-skin. The method identifies two defined boundaries on OCT skin images in order to measure ET. We applied CNN-GS-skin to OCT skin images, taken from various body sites of 63 healthy individuals. Compared with CNN-GS, our described method reduced computation time by 130 [Formula: see text] with minimal reduction in ET determination accuracy (from 96.38 to 94.67%).

Photoacoustic imaging for cutaneous melanoma assessment: a comprehensive review

Significance

Cutaneous melanoma (CM) has a high morbidity and mortality rate, but it can be cured if the primary lesion is detected and treated at an early stage. Imaging techniques such as photoacoustic (PA) imaging (PAI) have been studied and implemented to aid in the detection and diagnosis of CM.

Aim

Provide an overview of different PAI systems and applications for the study of CM, including the determination of tumor depth/thickness, cancer-related angiogenesis, metastases to lymph nodes, circulating tumor cells (CTCs), virtual histology, and studies using exogenous contrast agents.

Approach

A systematic review and classification of different PAI configurations was conducted based on their specific applications for melanoma detection. This review encompasses animal and preclinical studies, offering insights into the future potential of PAI in melanoma diagnosis in the clinic.

Results

PAI holds great clinical potential as a noninvasive technique for melanoma detection and disease management. PA microscopy has predominantly been used to image and study angiogenesis surrounding tumors and provide information on tumor characteristics. Additionally, PA tomography, with its increased penetration depth, has demonstrated its ability to assess melanoma thickness. Both modalities have shown promise in detecting metastases to lymph nodes and CTCs, and an all-optical implementation has been developed to perform virtual histology analyses. Animal and human studies have successfully shown the capability of PAI to detect, visualize, classify, and stage CM.

Conclusions

PAI is a promising technique for assessing the status of the skin without a surgical procedure. The capability of the modality to image microvasculature, visualize tumor boundaries, detect metastases in lymph nodes, perform fast and label-free histology, and identify CTCs could aid in the early diagnosis and classification of CM, including determination of metastatic status. In addition, it could be useful for monitoring treatment efficacy noninvasively.

Optical coherence tomography confirms non-malignant pigmented lesions in phacomatosis pigmentokeratotica using a support vector machine learning algorithm

INTRODUCTION

Phacomatosis pigmentokeratotica (PPK), an epidermal nevus syndrome, is characterized by the coexistence of nevus spilus and nevus sebaceus. Within the nevus spilus, an extensive range of atypical nevi of different morphologies may manifest. Pigmented lesions may fulfill the ABCDE criteria for melanoma, which may prompt a physician to perform a full-thickness biopsy.

MOTIVATION

Excisions result in pain, mental distress, and physical disfigurement. For patients with a significant number of nevi with morphologic atypia, it may not be physically feasible to biopsy a large number of lesions. Optical coherence tomography (OCT) is a non-invasive imaging modality that may be used to visualize non-melanoma and melanoma skin cancers.

MATERIALS AND METHOD

In this study, we used OCT to image pigmented lesions with morphologic atypia in a patient with PPK and assessed their quantitative optical properties compared to OCT cases of melanoma. We implement a support vector machine learning algorithm with Gabor wavelet transformation algorithm during post-image processing to extract optical properties and calculate attenuation coefficients.

RESULTS

The algorithm was trained and tested to extract and classify textural data.

CONCLUSION

We conclude that implementing this post-imaging machine learning algorithm to OCT images of pigmented lesions in PPK has been able to successfully confirm benign optical properties. Additionally, we identified remarkable differences in attenuation coefficient values and tissue optical characteristics, further defining separating benign features of pigmented lesions in PPK from malignant features.

Noninvasive imaging exploration of phacomatosis pigmentokeratotica using high-frequency ultrasound and optical coherence tomography: Can biopsy of PPK patients be avoided?

BACKGROUND

Phacomatosis pigmentokeratotica (PPK) is a distinct and rare type of epidermal nevus syndrome characterized by coexisting nonepidermolytic organoid sebaceous nevus (SN) with one or more speckled lentiginous nevi (SLN). Atypical nevi including compound Spitz and compound dysplastic may manifest within regions of SLN. Patients with PPK, or similar atypical nevus syndromes, may be subject to a significant lifetime number of biopsies, leading to pain, scarring, anxiety, financial burden, and decreased quality of life. The current literature includes case reports, genetics, and associated extracutaneous symptoms of PPK, but use of noninvasive imaging techniques have not been explored. We aim to investigate the value of high-frequency ultrasound (HFUS) and optical coherence tomography (OCT) in discriminating morphological features of pigmented lesions and nevus sebaceous within one patient with PPK.

MATERIALS AND METHODS

Two modalities, (1) HFUS imaging, based on acoustic properties and (2) OCT imaging, based on optical properties, were used to image a patient with PPK. Benign pigmented lesions, which may raise clinical suspicion for significant atypia, and nevus sebaceous, were selected on different areas of the body to be studied.

RESULTS

Five pigmented lesions and one area of nevus sebaceous were imaged and analyzed for noninvasive features. Distinct patterns of hypoechoic features were seen on HFUS and OCT.

CONCLUSION

HFUS provides a deep view of the tissue, with ability to differentiate gross structures beneath the skin. OCT provides a smaller penetration depth and a higher resolution. We have described noninvasive features of atypical nevi and nevus sebaceous on HFUS and OCT, which indicate benign etiology.

Mechanical modeling and characterization of human skin: A review

This paper reviews the advances made in recent years on modeling approaches and experimental techniques to characterize the mechanical properties of human skin. The skin is the largest organ of the human body that has a complex multi-layered structure with different mechanical behaviors. The mechanical properties of human skin play an important role in distinguishing between healthy and unhealthy skin. Furthermore, knowing these mechanical properties enables computer simulation, skin research, clinical studies, as well as diagnosis and treatment monitoring of skin diseases. This paper reviews the recent efforts on modeling skin using linear, nonlinear, viscoelastic, and anisotropic materials. The work also focuses on aging effects, microstructure analysis, and non-invasive methods for skin testing. A detailed explanation of the skin structure and numerical models, such as finite element models, are discussed in this work. This work also compares different experimental methods that measure the mechanical properties of human skin. The work reviews the experimental results in the literature and shows how the mechanical properties of human skin vary with the skin sites, the layers, and the structure of human skin. The paper also discusses how state-of-the-art technology can advance skin research.

Structural similarity assessment of an optical coherence tomographic image enhanced using the wavelet transform technique

We report on the quality assessment of an optical coherence tomography (OCT) image. A set of recent digital filters are used for denoising the interferometric signals. It is found that when a combination of continuous wavelet transform (WT) decomposition and the WT denoising techniques is imposed on raw signals, the highest signal-to-noise ratio of 17.8 can be reached. The structural similarity (SSIM) index is eventually employed to evaluate the modality of the reconstructed OCT image. Further, we found out that a SSIM value of about 0.95 can be reached, independent of the method used for envelope extraction.

Melanoma Biomarkers and Their Potential Application for In Vivo Diagnostic Imaging Modalities

Melanoma is the deadliest form of skin cancer and remains a diagnostic challenge in the dermatology clinic. Several non-invasive imaging techniques have been developed to identify melanoma. The signal source in each of these modalities is based on the alteration of physical characteristics of the tissue from healthy/benign to melanoma. However, as these characteristics are not always sufficiently specific, the current imaging techniques are not adequate for use in the clinical setting. A more robust way of melanoma diagnosis is to "stain" or selectively target the suspect tissue with a melanoma biomarker attached to a contrast enhancer of one imaging modality. Here, we categorize and review known melanoma diagnostic biomarkers with the goal of guiding skin imaging experts to design an appropriate diagnostic tool for differentiating between melanoma and benign lesions with a high specificity and sensitivity.

Combining Deep Learning With Optical Coherence Tomography Imaging to Determine Scalp Hair and Follicle Counts

BACKGROUND AND OBJECTIVES

One of the challenges in developing effective hair loss therapies is the lack of reliable methods to monitor treatment response or alopecia progression. In this study, we propose the use of optical coherence tomography (OCT) and automated deep learning to non-invasively evaluate hair and follicle counts that may be used to monitor the success of hair growth therapy more accurately and efficiently.

STUDY DESIGN/MATERIALS AND METHODS

We collected 70 OCT scans from 14 patients with alopecia and trained a convolutional neural network (CNN) to automatically count all follicles present in the scans. The model is based on a dual approach of both detecting hair follicles and estimating the local hair density in order to give accurate counts even for cases where two or more adjacent hairs are in close proximity to each other.

RESULTS

We evaluate our system on 70 OCT manually labeled scans taken at different scalp locations from 14 patients, with 20 of those redundantly labeled by two human expert OCT operators. When comparing the individual human predictions and considering the exact locations of hair and follicle predictions, we find that the two human raters disagree with each other on approximately 22% of hairs and follicles. Overall, the deep learning (DL) system predicts the number of follicles with an error rate of 11.8% and the number of hairs with an error rate of 18.7% on average on the 70 scans. The OCT system can capture one scalp location in three seconds, and the DL model can make all predictions in less than a second after processing the scan, which takes half a minute using an unoptimized implementation.

CONCLUSION

This approach is well-positioned to become the standard for non-invasive evaluation of hair growth treatment progress in patients, saving significant amounts of time and effort compared with manual evaluation. Lasers Surg. Med. © 2020 Wiley Periodicals, Inc.

Optical Coherence Tomography in the Evaluation of the Scalp and Hair: Common Features and Clinical Utility

BACKGROUND AND OBJECTIVE

Early diagnosis and treatment of hair loss disorders is vital in providing patients with improved psychological outcomes. Non-invasive imaging with optical coherence tomography (OCT) may be useful in characterizing and managing alopecia. Despite expanding clinical applications of OCT in dermatology, guidelines demonstrating in vivo features of normal and alopecic scalp images remain scant. This pilot study aims to provide an atlas of OCT findings of healthy and alopecia subjects, explore diagnostic quantitative endpoints of alopecia, and compare epidermal thickness and follicular density between scalp regions.

STUDY DESIGN/MATERIALS AND METHODS

A total of 32 patients (19-76 years old) were enrolled in the study, including healthy patients (n = 6), and patients with scarring alopecia (n = 12) or non-scarring alopecia (n = 14). An in-line fiber-based swept source OCT was used to image five scalp locations at baseline and 6-month visits. Three investigators evaluated each image for gross features, epidermal thickness, and follicular density.

RESULTS

Only data from baseline imaging analysis is discussed in this manuscript. Qualitative differences of OCT images are identified in sample images from healthy scalp and each subtype of alopecia studied. Scarring alopecia is characterized by significantly increased epidermal thickness (average Image J pixel units 32 ± 2 compared with non-scarring alopecia [average 28 ± 3] and control [average 27 ± 3]) (P = 0.022) and decreased follicle count (average 35 ± 5 in a 5 × 7 mm² area compared with control (50 ± 3) and non-scarring patients (47 ± 6)) (P = 0.0052). Scalp location had no impact on epidermal thickness (P = 0.861) or follicular density (P = 0.15).

CONCLUSION

OCT holds promise as a non-invasive technique to further characterize and objectively measure alopecia. Larger sample sizes and longitudinal data are needed to improve reliability and determine if additional distinction between alopecia subtypes and treatment monitoring is possible. Lasers Surg. Med. © 2020 Wiley Periodicals, Inc.

Photoacoustic/Ultrasound/Optical Coherence Tomography Evaluation of Melanoma Lesion and Healthy Skin in a Swine Model

The marked increase in the incidence of melanoma coupled with the rapid drop in the survival rate after metastasis has promoted the investigation into improved diagnostic methods for melanoma. High-frequency ultrasound (US), optical coherence tomography (OCT), and photoacoustic imaging (PAI) are three potential modalities that can assist a dermatologist by providing extra information beyond dermoscopic features. In this study, we imaged a swine model with spontaneous melanoma using these modalities and compared the images with images of nearby healthy skin. Histology images were used for validation.

An Application of Simulated Annealing in Compensation of Nonlinearity of Scanners

Galvo scanners are popular devices for fast transversal scanning. A triangular signal is usually employed to drive galvo scanners at scanning rates close to the inverse of their response time where scanning deflection becomes a nonlinear function of applied voltage. To address this, the triangular signal is synthesized from several short ramps with different slopes. An optimization algorithm similar to a simulated annealing algorithm is used for finding the optimal signal shape to drive the galvo scanners. As a result, a significant reduction in the nonlinearity of the galvo scanning is obtained.

Optical Radiomic Signatures Derived from Optical Coherence Tomography Images Improve Identification of Melanoma

The current gold standard for clinical diagnosis of melanoma is excisional biopsy and histopathologic analysis. Approximately 15-30 benign lesions are biopsied to diagnose each melanoma. In addition, biopsies are invasive and result in pain, anxiety, scarring, and disfigurement of patients, which can add additional burden to the health care system. Among several imaging techniques developed to enhance melanoma diagnosis, optical coherence tomography (OCT), with its high-resolution and intermediate penetration depth, can potentially provide required diagnostic information noninvasively. Here, we present an image analysis algorithm, "optical properties extraction (OPE)," which improves the specificity and sensitivity of OCT by identifying unique optical radiomic signatures pertinent to melanoma detection. We evaluated the performance of the algorithm using several tissue-mimicking phantoms and then tested the OPE algorithm on 69 human subjects. Our data show that benign nevi and melanoma can be differentiated with 97% sensitivity and 98% specificity. These findings suggest that the adoption of OPE algorithm in the clinic can lead to improvements in melanoma diagnosis and patient experience. SIGNIFICANCE: This study describes a noninvasive, safe, simple-to-implement, and accurate method for the detection and differentiation of malignant melanoma versus benign nevi.

Cluster-based filtering framework for speckle reduction in OCT images

Optical coherence tomography (OCT) has become a popular modality in the dermatology discipline due to its moderate resolution and penetration depth. OCT images, however, contain a grainy pattern called speckle. To date, a variety of filtering techniques have been introduced to reduce speckle in OCT images. However, further improvement is required to reduce edge smoothing and the deterioration of small structures in OCT images after despeckling. In this manuscript, we present a novel cluster-based speckle reduction framework (CSRF) that consists of a clustering method, followed by a despeckling method. Since edges are borders of two adjacent clusters, the proposed framework leaves the edges intact. Moreover, the multiplicative speckle noise could be modeled as additive noise in each cluster. To evaluate the performance of CSRF and demonstrate its generic nature, a clustering method, namely k-means (KM), and, two pixelwise despeckling algorithms, including Lee filter (LF) and adaptive Wiener filter (AWF), are used. The results indicate that CSRF significantly improves the performance of despeckling algorithms. These improvements are evaluated on healthy human skin images in vivo using two numerical assessment measures including signal-to-noise ratio (SNR), and structural similarity index (SSIM).

Role of modern imaging techniques for the in vivo diagnosis of lichen planus

Lichen planus (LP) is a chronic inflammatory skin disease that can sometimes affect mucosal surfaces, with unknown pathogenesis, even though it appears to be an autoimmune disease. The diagnosis of lichen planus is usually based on histopathological examination of the lesions. Nowadays, the classical invasive diagnostic methods are replaced by modern non-invasive techniques. In this review, we present the main non-invasive imaging methods (dermoscopy, reflectance confocal microscopy, optical coherence tomography, ultrasound and diffuse reflection spectrophotometry) used in the diagnosis and therapeutic monitoring of lichen planus. Dermoscopy is a non-invasive method initially used for diagnosis of pigmented tumors but now is used also for inflammatory and infectious skin diseases. In lichen planus, the dermoscopy increases the accuracy of diagnosis, avoids skin biopsies commonly used and can be useful in the therapeutic monitoring by repeated investigation at different stages of treatment. Reflectance confocal microscopy (RCM) is a novel non-invasive imaging technique that is prevalently used for the diagnosis of skin tumors and inflammatory skin diseases. This technology has been mostly employed for bedside, real-time microscopic evaluation of psoriasis, lichen planus, contact dermatitis, revealing specific confocal features to support clinical diagnosis and assist with patient management. Optical coherence tomography (OCT) is an emergent imaging technique, developed over the last decade, based on the interaction of the infrared radiation (900–1,500 nm) and the living tissues. A limited information exists on the benefits of OCT technology for the in vivo diagnosis of LP but could be a useful auxiliary tool in the in vivo differential diagnosis, especially in clinical equivocal settings like mucosal lesions, and in monitoring the response to treatment. Our review shows the possibility of using modern imaging techniques for the in vivo diagnosis and also for evaluation of the treatment response.

Granular Cell Tumor Imaging Using Optical Coherence Tomography

BACKGROUND

Granular cell tumor (GCT) is a relatively uncommon tumor that may affect the skin. The tumor can develop anywhere on the body, although it is predominately seen in oral cavities and in the head and neck regions. Here, we present the results of optical coherence tomography (OCT) imaging of a large GCT located on the abdomen of a patient. We also present an analytical method to differentiate between healthy tissue and GCT tissues.

MATERIALS AND METHODS

A multibeam, Fourier domain, swept source OCT was used for imaging. The OCT had a central wavelength of 1305 ± 15 nm and lateral and axial resolutions of 7.5 and 10 µm, respectively. Qualitative and quantitative analyses of the tumor and healthy skin are reported.

RESULTS

Abrupt changes in architectures of the dermal and epidermal layers in the GCT lesion were observed. These architectural changes were not observed in healthy skin.

DISCUSSION

To quantitatively differentiate healthy skin from tumor regions, an optical attenuation coefficient analysis based on single-scattering formulation was performed. The methodology introduced here could have the capability to delineate boundaries of a tumor prior to surgical excision.

Development and Optimization of a Fluorescent Imaging System to Detect Amyloid-β Proteins: Phantom Study

Alzheimer disease is the most common form of dementia, affecting more than 5 million people in the United States. During the progression of Alzheimer disease, a particular protein begins to accumulate in the brain and also in extensions of the brain, ie, the retina. This protein, amyloid-β (Aβ), exhibits fluorescent properties. The purpose of this research article is to explore the implications of designing a fluorescent imaging system able to detect Aβ proteins in the retina. We designed and implemented a fluorescent imaging system with a range of applications that can be reconfigured on a fluorophore to fluorophore basis and tested its feasibility and capabilities using Cy5 and CRANAD-2 imaging probes. The results indicate a promising potential for the imaging system to be used to study the Aβ biomarker. A performance evaluation involving ex vivo and in vivo experiments is planned for future study.

Clinical translation of handheld optical coherence tomography: practical considerations and recent advancements

Since the inception of optical coherence tomography (OCT), advancements in imaging system design and handheld probes have allowed for numerous advancements in disease diagnostics and characterization of the structural and optical properties of tissue. OCT system developers continue to reduce form factor and cost, while improving imaging performance (speed, resolution, etc.) and flexibility for applicability in a broad range of fields, and nearly every clinical specialty. An extensive array of components to construct customized systems has also become available, with a range of commercial entities that produce high-quality products, from single components to full systems, for clinical and research use. Many advancements in the development of these miniaturized and portable systems can be linked back to a specific challenge in academic research, or a clinical need in medicine or surgery. Handheld OCT systems are discussed and explored for various applications. Handheld systems are discussed in terms of their relative level of portability and form factor, with mention of the supporting technologies and surrounding ecosystem that bolstered their development. Additional insight from our efforts to implement systems in several clinical environments is provided. The trend toward well-designed, efficient, and compact handheld systems paves the way for more widespread adoption of OCT into point-of-care or point-of-procedure applications in both clinical and commercial settings.

An overview of methods to mitigate artifacts in optical coherence tomography imaging of the skin

BACKGROUND

Optical coherence tomography (OCT) of skin delivers three-dimensional images of tissue microstructures. Although OCT imaging offers a promising high-resolution modality, OCT images suffer from some artifacts that lead to misinterpretation of tissue structures. Therefore, an overview of methods to mitigate artifacts in OCT imaging of the skin is of paramount importance. Speckle, intensity decay, and blurring are three major artifacts in OCT images. Speckle is due to the low coherent light source used in the configuration of OCT. Intensity decay is a deterioration of light with respect to depth, and blurring is the consequence of deficiencies of optical components.

METHOD

Two speckle reduction methods (one based on artificial neural network and one based on spatial compounding), an attenuation compensation algorithm (based on Beer-Lambert law) and a deblurring procedure (using deconvolution), are described. Moreover, optical properties extraction algorithm based on extended Huygens-Fresnel (EHF) principle to obtain some additional information from OCT images are discussed.

RESULTS

In this short overview, we summarize some of the image enhancement algorithms for OCT images which address the abovementioned artifacts. The results showed a significant improvement in the visibility of the clinically relevant features in the images. The quality improvement was evaluated using several numerical assessment measures.

CONCLUSION

Clinical dermatologists benefit from using these image enhancement algorithms to improve OCT diagnosis and essentially function as a noninvasive optical biopsy.