An improved algorithm of structural image reconstruction with rapid scanning optical delay line for Optical Coherence Tomography

Petrov, Denis; Abdulkareem, Saif N.; Ghaleb, Kamal E. S.; Proskurin, Sergey G.

doi:10.18287/jbpe16.02.020302

Cited by 2 publications

(2 citation statements)

References 16 publications

(16 reference statements)

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“…This speckle noise is a ubiquitous artifact that limits the interpretation as it profoundly affects the quality, contrast of the image and makes the difficulties in analyzing the exceptional features and structures. The back reflections of the incident light generates a signal which carries speckle, while due to scattering of photons in forwarding and backward direction generates the signal-degrading speckle (Petrov et al, 2016). The speckle is visible as grainy structures which blurs the details of the structural image (Murakami & Ogawa, 2018).…”

Section: Image Processing In Octmentioning

confidence: 99%

“…The final images of choriocapillaris give information regarding the diseases and the response of the body to therapies. Petrov et al (2016) applied the short time Fourier transforms in the signal processing, using the window and this window slid along the time series. This algorithm takes more time to execute as it is having more point FFT, also we see the maximum penetration depth is not much and if we want to image the tissue to certain depth we need more penetration depth (Petrov et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

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Algorithm for B-scan Image Reconstruction in Optical Coherence Tomography

Patil¹,

Mahajan²,

Subramani³

et al. 2021

JST

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Optical coherence tomography (OCT) is an evolving medical imaging technology that offers in vivo cross-sectional, sub-surface images in real-time. OCT has become popular in the medical as well as non-medical fields. The technique extensively uses for food industry, dentistry, dermatology, and ophthalmology. The technique is non-invasive and works on the Michelson interferometry principle, i.e., dependent on back reflections of the signal and its interference. The objective is to develop an algorithm for signal processing to construct an OCT image and then to enhance the quality of the image using image processing techniques like filtering. The image construction was primarily based on the Fourier transform (FT) of the dataset obtained by data acquisition. This FT could be performed rapidly with the extensively used algorithm of fast Fourier transform (FFT). The depth-wise information could be extracted from each A-scan, i.e., axial scan and also the B-scan was obtained from the A-scan to see the structure of sample. The maximum penetration depth achieved with proposed system was 2.82mm for 1024 data points. First and second layer of leaf were getting at thickness of 1mm and 1.6mm, respectively. A-scans for Human fingertip gave its first, second and third layer was at a thickness of 0.75mm, 0.9mm and 1.6mm, respectively. A-scans for foam sheet gave its first, second and third layer was at a thickness of 0.6mm, 0.75mm, and 0.85mm, respectively.

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Section: Image Processing In Octmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%