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1

Imaging the retinal and choroidal vasculature using Spatio-Temporal Optical Coherence Tomography (STOC-T)

Liżewski Kamil, Tomczewski Slawomir, Borycki Dawid, Węgrzyn Piotr, Wojtkowski Maciej

Biocybernetics and Biomedical Engineering

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2024

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Vol. 44, no. 1

95--104

EN

Spatio-Temporal Optical Coherence Tomography (STOC-T) is a novel imaging technique using light with controlled spatial and temporal coherence. Retinal images obtained using the STOC-T system maintain high resolution in all three dimensions, on a sample of about 700 μm, without the need for mechanical scanning. In the present work, we use known data processing algorithms for optical coherence tomography angiography (OCTA) and modify them to improve the rendering of the vasculature in the human retina at different depths by introducing the angio STOC-T method. The algorithms are primarily sensitive to the strong signal phase variance corresponding to the appearance of a wide Doppler band in STOC-T signals obtained for millisecond exposure times. After using STOC-T angiography, we can render high contrast images of the choroid.

2

Common path optical coherence tomography with electronic feedback for improved sensitivity

Alsnaie Khalid

Optica Applicata

|

2023

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Vol. 53, nr 3

495--504

EN

Optical coherence tomography (OCT) imaging has become a useful tool in medical diagnosis over the past 25 years, because of its ability to visualize intracellular structures at high resolution. The main objective of this work is to add electronic feedback to the optical coherence tomography setup to increase its sensitivity. Noise added to the measured interferogram obscures some details of examined tissue layered structure. Adjusting signal power level in such a way to improve signal-to-noise ratio can help to enhance image quality. Electronic feedback is added to enhance system sensitivity. A logarithmic amplifier is included in the OCT setup to automatically adapt signal level. Moreover, the resolution of the optical spectrum analyzer is controlled according to the farthest layer detected in the A-scan. These techniques are tested showing an improvement in obtained image of a human nail.

3

Computer aided diagnosis of diabetic macular edema in retinal fundus and OCT images: A review

Pavithra K.C., Kumar Preetham, Geetha M., Bhandary Sulatha V.

Biocybernetics and Biomedical Engineering

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2023

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Vol. 43, no. 1

157--188

EN

Diabetic Macular Edema (DME) is a potentially blinding consequence of Diabetic Retinopathy (DR) as well as the leading cause of vision loss in diabetics. DME is characterized by a buildup of extracellular fluid inside the macula through hyperpermeable vessels. The presence of DME can be spotted at any level of DR with varying degrees of severity using prominent imaging modalities such as Color Fundus Photography (CFP) and Optical Coherence Tomography (OCT). Computerized approaches for screening eye disorders appear to be beneficial, as they provide doctors with detailed insights into abnormalities. Such a system for the evaluation of retinal images can function as a stand-alone disease monitoring system. This review reports the state-of-art automated DME detection methods with traditional Machine Learning (ML) and Deep Learning (DL) techniques employing retinal fundus or OCT images. The paper provides a list of public retinal OCT and fundus imaging datasets for DME detection. In addition, the paper describes the dynamics of advancements in presented methods adopted in the past along with their strengths and limitations to highlight the insufficiencies that could be addressed in future investigations.

4

Use of dominant activations obtained by processing OCT images with the CNNs and slime mold method in retinal disease detection

Toğaçar Mesut, Ergen Burhan, Tümen Vedat

Biocybernetics and Biomedical Engineering

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2022

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Vol. 42, no. 2

646--666

EN

Retinal disease is one of the diseases that cause visual symptoms or loss of vision in humans. This disease can affect the choroid, which severely affects vision. Optical coherence tomography (OCT) images are usually used to detect retinal disease. OCT is an imaging technique that takes high-resolution slices of retinal images. It takes time for experts to examine and interpret the OCT images. Experts need to take advantage of technological capabilities to make this process faster and more accurate. Three datasets were used in this study. Dataset #1 (UCSD dataset) consists of choroidal neovascularization (CNV), diabetic macular edema (DME), drusen, and normal OCT image types. Dataset #2 (Duke dataset) and Dataset #3 consist of age-related macular degeneration (AMD), DME, and normal OCT image types. An artificial intelligence based hybrid approach was proposed for retinal disease detection. In the proposed approach, class-based activations were extracted for each model with nine transfer learning models using the dataset. Next, the dominant activations were selected from the model-based activations of each class using the slime mold algorithm (SMA) and the selected activations were classified using the softmax method. The overall accuracy obtained in classification is as follows: 99.60% for dataset 1, 99.89% for dataset #2 and 97.49% for dataset #3. In this study, it was found that the proposed approach contributes to the performance of transfer learning models.

5

Detection of petroleum products using optical coherence tomography

Kamińska Aleksandra M., Pluciński Jerzy

Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej

|

2021

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Nr 73

27--30

EN

In this work, we present a novel method developed for the analysis of the properties of thin layers for detecting petroleum products on a water surface using a commercially available optical coherence tomography (OCT) system. The spectral density analysis of the signal from a spectroscopic OCT (S-OCT) enables us to perform the precision calculation of the thin layer thickness and other properties like homogeneity, and dispersion, even if layer thickness is smaller than the coherence length of light from the used broadband light source. Mathematical modeling has been confirmed by measurements. The experiment with thin oil films on the surface of the water was conducted. The obtained results indicate that it is possible to measure the thickness of the petroleum product layers on the surface of the water smaller than 1 μm with 10 nm resolution.

PL

W pracy przedstawiono nowatorską metodę analizy właściwości cienkich warstw przy użyciu standardowych dostępnych na rynku systemów optycznej tomografii koherentnej (ang. optical coherence tomography – OCT) na potrzeby wykrywania produktów naftowych na powierzchni wody. Analiza gęstości widmowej mocy sygnału pochodzącego z systemu OCT z detekcją spektroskopową (ang. spectroscopic OCT – S-OCT) pozwala na dokładne obliczenie grubości cienkiej warstwy i innych jej właściwości, takich jak jednorodność i dyspersja, nawet jeśli grubość warstwy jest mniejsza niż długość drogi koherencji stosowanego szerokopasmowego źródła światła. Wyniki działania systemu uzyskane metodą modelowania matematycznego zostały potwierdzone pomiarami uzyskanymi z komercyjnego systemu, wykorzystując zaawansowane metody przetwarzania sygnałów. Przeprowadzono eksperyment z cienkimi warstwami olejowymi na powierzchni wody. Na podstawie uzyskanych wyników można stwierdzić, że możliwy jest pomiar grubości warstwy produktu ropopochodnego na powierzchni wody cieńszej niż 1 μm przy rozdzielczości pomiarów 10 nm.

6

Graph-based segmentation with homogeneous hue and texture vertices

Ngo Lua, Han Jae-Ho

Optica Applicata

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2021

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Vol. 51, nr 4

541--549

EN

This work presents an automated segmentation method, based on graph theory, which processes superpixels that exhibit spatially similarities in hue and texture pixel groups, rather than individual pixels. The graph shortest path includes a chain of neighboring superpixels which have minimal intensity changes. This method reduces graphics computational complexity because it provides large decreases in the number of vertices as the superpixel size increases. For the starting vertex prediction, the boundary pixel in first column which is included in this starting vertex is predicted by a trained deep neural network formulated as a regression task. By formulating the problem as a regression scheme, the computational burden is decreased in comparison with classifying each pixel in the entire image. This feasibility approach, when applied as a preliminary study in electron microscopy and optical coherence tomography images, demonstrated high measures of accuracy: 0.9670 for the electron microscopy image and 0.9930 for vitreous/nerve-fiber and inner-segment/outer-segment layer segmentations in the optical coherence tomography image.

7

Segmentation of anterior segment boundaries in swept source OCT images

Garcia Marin Yoel, Skrok Marta, Siedlecki Damian, Vincent Stephen J., Collins Michael J., Alonso-Caneiro David

Biocybernetics and Biomedical Engineering

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2021

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Vol. 41, no. 3

903--915

EN

Quantification of the eye’s anterior segment morphology from optical coherence tomography (OCT) images is crucial for research and clinical decision-making, including the diagnosis and monitoring of many ocular diseases. Structural parameters, such as tissue thickness and area are the most common metrics used to quantify these medical images, and tissue segmentation is required before these metrics can be extracted. Currently, swept source OCTallows the capture of cross-sectional images that encompass the entire anterior segment with a high level of detail. However, the manual annotation of tissue boundaries is time-consuming. In this work, an algorithm based on graph-search theory combined with boundary-specific image transformation is applied for the segmentation of anterior segment OCT images. We demonstrate that the method can reliably segment 5 different tissue boundaries in healthy eyes with low boundary error (mean error below 1 pixel across all boundaries). The technique can be used to extract clinically relevant parameters such as central corneal and crystalline lens thickness as well as anterior chamber depth and area, with a high level of agreement with manual segmentation (normalized errors below 1.6%). The proposed method provides a tool that can support clinical and research OCT data analysis.

8

Optical coherence tomography image for automatic classification of diabetic macular edema

Wang Ping, Li Jia-Li, Ding Hao

Optica Applicata

|

2020

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Vol. 50, nr 4

567--577

EN

Diabetic macular edema (DME) is the dominant reason of diabetic visual loss, so early detection and treatment of DME is of great significance for the treatment of diabetes. Based on transfer learning, an automatic classification method is proposed to distinguish DME images from normal images in optical coherence tomography (OCT) retinal fundus images. Features of the DME are automatically identified and extracted by the pre-trained convolutional neural network (CNN), which only involves fine-tuning the VGGNet-16 network without any user intervention. An accuracy of 97.9% and a sensitivity of 98.0% are acquired with the OCT images in the Duke data set from experimental results. The proposed method, a core part of an automated diagnosis system of the DME, revealed the ability of fine-tuning models to train non-medical images, allowing them can be classified with limited training data. Moreover, it can be developed to assist early diagnosis of the disease, effectively delaying (or avoiding) the progression of the disease, consequently.

9

Intraoperative imaging based on common-path time-domain reflectometry for brain tumor surgery

Han Jae-Ho, Cha Jaepyeong

Optica Applicata

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2020

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Vol. 50, nr 2

223--227

EN

Minimally invasive intraoperative imaging plays a crucial role in delicate microsurgeries for precise operation monitoring in which fiber optic imaging can be considered as an endoscopy and surgical proximity guidance tool due to its compactness. This paper presents a near-infrared time-domain reflectometric common-path optical coherence tomography imaging technique using a bare-fiber probe mounted directly on a scanning galvanometer. The common-path setup allows the use of a freely adjustable optical path length and a disposable fiber probe, as well as eliminating the need for an additional dedicated reference optical path. Experimental results demonstrate clear discrimination between the brain tumor tissue and the normal tissue for mouse brains with the images acquired in real-time over a wide area. The proposed method enables real-time and in situ visualization of tumor resection for intraoperative imaging, and this study demonstrates the feasibility of its application to microsurgical interventions.

10

Stack generalized deep ensemble learning for retinal layer segmentation in Optical Coherence Tomography images

Anoop B. N., Pavan Rakesh, Girish G. N., Kothari Abhishek R., Rajan Jeny

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 4

1343--1358

EN

Segmentation of retinal layers is a vital and important step in computerized processing and the study of retinal Optical Coherence Tomography (OCT) images. However, automatic segmentation of retinal layers is challenging due to the presence of noise, widely varying reflectivity of image components, variations in morphology and alignment of layers in the presence of retinal diseases. In this paper, we propose a Fully Convolutional Network (FCN) termed as DelNet based on a deep ensemble learning approach to selectively segment retinal layers from OCT scans. The proposed model is tested on a publicly available DUKE DME dataset. Comparative analysis with other state-of-the-art methods on a benchmark dataset shows that the performance of DelNet is superior to other methods.

11

Wpływ oddziaływania wiązki laserowej na skłonność tkanin poliestrowych do pilingu

Korzeniewska Ewa, Walczak Maria, Sekulska-Nalewajko Joanna, Gocławski Jarosław

Przegląd Elektrotechniczny

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2019

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R. 95, nr 1

73--76

PL

W artykule opisano wpływ modyfikacji powierzchni tkanin poliestrowych z wykorzystaniem wiązki laserowej. Ocenę tendencji do pilingu wykonano w oparciu o analizę obrazów 2D oraz 3D pozyskanych z wykorzystaniem optycznego tomografu koherentnego. Zaobserwowano, pozytywny wpływ obróbki laserowej na zmniejszającą się liczbę poluzowanych pojedynczych nitek wystających ponad powierzchnię tkaniny, a w efekcie końcowym na zmniejszenie powstającego niepożądanego pilingu.

EN

In the article the effect of surface modification of polyester fabrics using a laser beam has been described. Pilling tendency have been assessed based on the analysis of 2D and 3D images obtained from the optical coherence tomography. A positive effect of laser processing has been observed on the decreasing number of loosened single threads protruding above the surface of the fabric and in the result the reduction of the unwanted pilling.

12

Measurement of retina vessels by segmentation of images reconstructed from optical coherence tomography data

Marciniak Tomasz, Stankiewicz Agnieszka, Dąbrowski Adam, Stopa Marcin, Rakowicz Piotr, Marciniak Elżbieta

Metrology and Measurement Systems

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2019

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Vol. 26, nr 3

449--461

EN

In this paper methods and their examination results for automatic segmentation and parameterization of vessels based on spectral domain optical coherence tomography (SD-OCT) of the retina are presented. We present three strategies for morphologic image processing of a fundus image reconstructed from OCT scans. A specificity of initial image processing for fundus reconstruction is analysed. Then, the parameterization step is performed based on the vessels segmented with the proposed algorithm. The influence of various methods on the vessel segmentation and fully automatic vessel measurement is analysed. Experiments were carried out with a set of 3D OCT scans obtained from 24 eyes (12 healthy volunteers) with the use of an Avanti RTvue OCT device. The results of automatic vessel segmentation were numerically compared with those prepared manually by the medical doctor experts.

13

Automated characterization and classification of coronary atherosclerotic plaques for intravascular optical coherence tomography

Yang Jianli, Zhang Bo, Wang Hongrui, Lin Feng, Han Yechen, Liu Xiuling

Biocybernetics and Biomedical Engineering

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2019

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Vol. 39, no. 3

719--727

EN

Identification of coronary atherosclerotic plaques and vulnerable plaques is of great clinical significance in the diagnosis and treatment of coronary artery diseases, such as myocardial infarction and sudden death. Optical coherence tomography (OCT) is a catheter-based intracoronary imaging technique with high resolution (<20 μm) adopted to study the morphology of atherosclerotic plaques and identification of the composition of plaques. Nevertheless, manual characterization and quantification of plaques by clinicians is a labor-intensive and subjective procedure. This study aimed to propose a novel plaque characterization algorithm to automatically characterize and classify the atherosclerotic plaques (fibrous, calcific, and lipid-rich). First, nongeometric features such as Fisher vector, principal component analysis, histogram of the oriented gradient, and local binary pattern were investigated and adapted to two geometric features (basic feature and texture feature) to characterize the plaques. Second, for automated classification of the plaques, a hard example mining strategy was introduced to train support vector machine classifier and improve the effectiveness of training data. Third, to demonstrate the relationship between the selected features and the plaque classification accuracy, different feature compositions and comparisons were presented. The contribution of key features to the final classification was revealed. Datasets from 20 OCT pullbacks of 9 patients were used in the training and testing using the proposed algorithm. The overall classification accuracy reached 96.8%, and that of fibrous, calcific, and lipid-rich plaques was 94%, 97.2%, and 99.2%, respectively.

14

Recognition of Weave Patterns of Striped Fabrics Using Optical Coherence Tomography

Sabuncu M., Özdemir H.

Fibres & Textiles in Eastern Europe

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2018

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Vol. 26, no. 3 (129)

98--103

EN

The recognition of woven fabric repeat by conventional techniques is labour intensive. In general, woven fabric repeat identification is accomplished automatically by employing complex algorithms and techniques. These algorithms may, however, occasionally fail, especially when dealing with high complexity texture patterns, structures, figures and colours. Optical coherence tomography (OCT) has the capability of taking high resolution images via contactless measurements. In this paper we apply the spectral domain optical coherence tomography imaging technique for identifying striped woven fabric repeat automatically. OCT scans corresponding to four different fabrics, from which the weave matrixes were recognised, are reported in this study. Automatic identification of weave patterns of striped fabrics was accomplished non-destructively by employing optical coherence tomography.

PL

Rozpoznanie powtórzenia tkaniny za pomocą konwencjonalnych technik jest pracochłonne. Ogólnie rzecz biorąc, identyfikacja powtórzenia tkaniny jest przeprowadzana automatycznie przez zastosowanie złożonych algorytmów i technik. Algorytmy te mogą jednak czasami zawieść, szczególnie w przypadku bardzo złożonych wzorów tekstur, struktur, figur i kolorów. Optyczna tomografia koherencyjna (OCT) ma zdolność wykonywania zdjęć o wysokiej rozdzielczości za pomocą pomiarów bezstykowych. W artykule zastosowano technikę obrazowania optycznego tomografii koherencji spektralnej do automatycznego rozpoznawania powtórzeń tkanin w paski. W badaniu przedstawiono skany OCT odpowiadające czterem różnym materiałom, z których rozpoznano matryce splotu. Automatyczna identyfikacja wzorów splotów tkanin w paski została przeprowadzona w sposób niedestrukcyjny dzięki zastosowaniu optycznej tomografii koherencyjnej.

15

The Detection of Internal Fingerprint Image Using Optical Coherence Tomography

Sekulska-Nalewajko J., Gocławski J., Sankowski D.

Image Processing & Communications

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2017

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Vol. 22, no. 4

59--72

EN

Recently, optical coherence tomography (OCT) has been tested as a contactless technique helpful for damaged or spoofed fingerprint recovery. Three dimensional OCT images cover the range from the skin surface to papillary region in upper dermis. The proposed method extracts from B-scans high intensity ridges in both air-epidermis and dermis-epidermis interfaces. The extraction is based on the localisation of two OCT signal peaks corresponding to these edges. The borders are spline smoothed in two orthogonal planes of the image space. The result images are presented and compared with camera views.

16

Wczoraj, dziś i jutro polskiej radiologii

Skrzyński W.

Inżynier i Fizyk Medyczny

|

2013

|

Vol. 2, nr 4

207--209

PL

W jednym z tegorocznych numerów „Inżyniera i Fizyka Medycznego” ukazał się artykuł o „(nie) znanej radiologii” [1]. Jego autorka w interesujący sposób przybliżyła czytelnikom dzieje polskiej radiologii – od jej początków, przez trudne lata II wojny światowej i PRL-u, aż po dzień dzisiejszy – a także perspektywy na przyszłość. Podążając tym samym tropem, chciałbym przypomnieć kilka faktów z pierwszych lat istnienia radiologii.

17

Non-destructive inspection of anti-corrosion protective coatings using optical coherent tomography

Antoniuk P., Strąkowski M. R., Pluciński J., Kosmowski B. B.

Metrology and Measurement Systems

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2012

|

Vol. 19, nr 2

365-372

EN

Optical Coherence Tomography (OCT) is one of the most rapidly advancing techniques. This method is capable of non-contact and non-destructive investigation of the inner structure of a broad range of materials. Compared with other methods which belong to the NDE/NDT group (Non-Destructive Evaluation/Non-Destructive Testing methods), OCT is capable of a broad range of scattering material structure visualization. Such a non-invasive and versatile method is very demanded by the industry. The authors applied the OCT method to examine the corrosion process in metal samples coated by polymer films. The main aim of the research was the evaluation of the anti-corrosion protective coatings using the OCT method. The tested samples were exposed to a harsh environment. The OCT measurements have been taken at different stages of the samples degradation. The research and tests results have been presented, as well as a brief discussion has been carried out.

18

Optyczna tomografia koherentna w badaniach technicznych obiektów rozpraszających

Strąkowski M., Pluciński J.

Zeszyty Naukowe Wydziału ETI Politechniki Gdańskiej. Technologie Informacyjne

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2010

|

T. 19

413-418

PL

Optyczna tomografia koherentna (OCT) jest nieinwazyjną i bezkontaktową metodą badania wewnętrznej struktury materiałów i obiektów rozpraszających promieniowanie optyczne. Technika ta jest jedną z bardziej zaawansowanych metod pomiarowych należących do dziedziny NDT (ang. non-destructive testing) i NDE (ang. non-destructive evaluation). Umożliwia ona lokalizowanie oraz badanie defektów występujących wewnątrz badanego obiektu. W artykule omówiono właściwości metody, zakres i możliwości metrologiczne oraz przykładowe aplikacje. Przedstawiono wyniki pomiarów uzyskanych dla materiałów o zróżnicowanych właściwościach optycznych. Na podstawie przeprowadzonych eksperymentów wykazano przydatność OCT do badania jakości wytworzonych elementów oraz monitorowania zmian związanych z degradacją struktury testowanego obiektu.

EN

Optical coherence tomography (OCT) is an optical method, witch enables non-contact and non-destructive examination of inner structure of scattering materials. OCT is a one of the most advanced methods in NDT (non-destructive testing) and NDE (non-destructive evaluation) branch. With the aid of OCT the surface and subsurface defects can be investigated. In this paper the OCT features and measurements abilities have been presented, as well as applications examples. Moreover, the measurement results obtained for scattering materials have been shown. Based on those results the usefulness of the OCT and OCT limits have been discussed.

19

Readout System and Data Processing for OCT Pachymetry

Dziewiecki M., Domański G., Frey W., Konarzewski B., Kurjata R., Marzec J., Smolnik A., Zaremba K., Ziembicki M.

International Journal of Electronics and Telecommunications

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2010

|

Vol. 56, No. 3

223-230

EN

A complete system for measurement control, signal acquisition and data processing for an OCT pachymeter is described. Moreover, dedicated data processing algorithm used for noise reduction is presented. A simple OCT scanner was built and some measurements were performed to examine the capabilities of the system.

20

Zastosowanie interferometrii niskokoherentnej do jednoczesnego pomiaru grubości i współczynnika załamania struktur warstwowych

Pluciński J., Strąkowski M., Kosmowski B. B.

Elektronika : konstrukcje, technologie, zastosowania

|

2010

|

Vol. 51, nr 6

136-139

PL

W pracy przedstawiono techniki oparte na interferometrii niskokoherentnej jednoczesnego pomiaru współczynnika załamania i grubości struktur warstwowych. Zaproponowano dwie metody: pierwsza oparta jest na pomiarze położenia górnej powierzchni granicznej warstwy i jej grubości optycznej (położenie dolnej powierzchni granicznej powinno być znane wcześniej); druga oparta jest na wykorzystaniu dynamicznego ogniskowania wiązki laserowej. Przeprowadzone testy pokazały, że możliwy jest jednoczesny pomiar grubości geometrycznej warstwy z dokładnością 1µm i współczynnika załamania z dokładnością lepszą niż 0,01.

EN

The paper presents a technique based on Iow-coherence interferometry for simultaneous measurement of refractive index and thickness of layered structures. Two methods are proposed: the first one is based on the measurement of the position of the upper boundary surface of the layer and its optical thickness (the position of the Iower boundary surface of the layer should be known in advance), the second one is based on dynamie focusing of the laser beam that is used in the measuring system. Performed tests have shown that it is possible to simultaneously measure the geometrie thickness with the accuracy of 1 µm, and the refractive index of better than 0.01.