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

• Published in: Skin research and technology 2018-05, Vol.24 (2), p.265-273
• Main Authors: Adabi, Saba, Fotouhi, Audrey, Xu, Qiuyun, Daveluy, Steve, Mehregan, Darius, Podoleanu, Adrian, Nasiriavanaki, Mohammadreza
• Format: Article
• Language: English
• Subjects: Algorithms; Artificial neural networks; Biopsy; Blurring; blurring correction; Coherent light; Decay; Extremely high frequencies; Image enhancement; Image quality; intensity decay compensation; Light sources; Luminous intensity; Medical imaging; Neural networks; Optical Coherence Tomography; Optical components; Optical properties; Planet detection; Quality control; Reviews; Skin; speckle reduction; Tomography
• ISSN: 0909-752X; 1600-0846
• DOI: 10.1111/srt.12423

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.