Depth-resolved model-based reconstruction of attenuation coefficients in optical coherence tomography

Vermeer, Koenraad A.; Mo, Jianhua; Weda, Jelmer J. A.; Lemij, Hans G; Boer, Johannes F. de

doi:10.1364/boe.5.000322

Cited by 297 publications

(339 citation statements)

References 30 publications

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“…6(c), 6(e) and 6(g) to color the noise area black. An attenuation coefficient image [53] that was created using the raw data of Fig. 6(a) is shown in Fig.…”

Section: Estimation Of H Noise At a Single Depthmentioning

confidence: 99%

Estimation of Jones matrix, birefringence and entropy using Cloude-Pottier decomposition in polarization-sensitive optical coherence tomography

Yamanari¹,

Tsuda²,

Kokubun³

et al. 2016

Biomed. Opt. Express

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Estimation of polarimetric parameters has been a fundamental issue to assess biological tissues that have form birefringence or polarization scrambling in polarizationsensitive optical coherence tomography (PS-OCT). We present a mathematical framework to provide a maximum likelihood estimation of the target covariance matrix and its incoherent target decomposition to estimate a Jones matrix of a dominant scattering mechanism, called Cloude-Pottier decomposition, thereby deriving the phase retardation and the optic axis of the sample. In addition, we introduce entropy that shows the randomness of the polarization property. Underestimation of the entropy at a low sampling number is mitigated by asymptotic quasi maximum likelihood estimator. A bias of the entropy from random noises is corrected to show only the polarization property inherent in the sample. The theory is validated with experimental measurements of a glass plate and waveplates, and applied to the imaging of a healthy human eye anterior segment as an image filter.

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“…6(c), 6(e) and 6(g) to color the noise area black. An attenuation coefficient image [53] that was created using the raw data of Fig. 6(a) is shown in Fig.…”

Section: Estimation Of H Noise At a Single Depthmentioning

confidence: 99%

Estimation of Jones matrix, birefringence and entropy using Cloude-Pottier decomposition in polarization-sensitive optical coherence tomography

Yamanari¹,

Tsuda²,

Kokubun³

et al. 2016

Biomed. Opt. Express

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“…The results of our work demonstrate that we can accurately segment the interfaces of corrugated thin layers. Our segmentation is based on the OCT AC image as determined with the model of Vermeer et al [25]. This model is known to be biased in the quantification of the attenuation coefficient.…”

Section: Discussionmentioning

confidence: 99%

“…The signal to noise ratio, determined from an OCT measurement of a single mirror reflector at 0.3 micrometer depth, is 92.4±0.5 dB. The attenuation coefficient image is obtained by correcting the OCT intensity signal for roll-off, subsequently followed by a depth integration [25]. In order to increase the SNR, every cross-sectional image in this work is an average of 10 B-scans.…”

Section: Oct Set-upmentioning

confidence: 99%

“…The initial segmentation is used as an initialization for our second step, the matching layer attenuation coefficient segmentation (MLAS). This segmentation method relies on the property that the value of the OCT attenuation coefficient (AC), as determined with the method of Vermeer et al [25], is constant in a layer. Based on this additional information the image is resegmented.…”

Section: Introductionmentioning

confidence: 99%

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Segmentation of thin corrugated layers in high-resolution OCT images

Callewaert¹,

Dik²,

Kalkman³

2017

Opt. Express

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Abstract:In this paper we present a novel method for the segmentation of thin corrugated layers in high resolution optical coherence tomography (OCT) images. First, we make an initial segmentation, for example with graph based segmentation that, for highly corrugated interfaces, leads to many segmentation errors. Second, we resegment the initial outcome, based on the OCT attenuation coefficient image with our matching layer attenuation coefficient segmentation (MLAS) algorithm. This algorithm repositions the initial segmentation such that it finds the point where the attenuation coefficient is close to the mean centerline attenuation. The algorithm does not utilize any sample specific prior knowledge in the attenuation coefficient based segmentation step. For simulated and measured data of strongly corrugated samples, such as is the case for varnish layers on paintings and furniture, the MLAS algorithm performs much better than the conventional segmentation. Finally, we show 3D segmentation of 190 mm 3 OCT volume of a thin corrugated varnish layer. Our technique can aid in the rapid characterization of layer stratigraphy and deepen our understanding of their condition.

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“…4(c)) it is possible to observe that the lamina propria and the submucosa appear as sharply defined, high intensity peaks, showing a rapid rise and fall of the OCT signal intensity. On the other hand, BE A-lines appear as a single layer of weakly attenuating tissue following an exponential decay [14,15].…”

Section: Tissue Characterizationmentioning

confidence: 99%

Automated segmentation and characterization of esophageal wall in vivo by tethered capsule optical coherence tomography endomicroscopy

Ughi¹,

Gora²,

Swager³

et al. 2016

Biomed. Opt. Express

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Optical coherence tomography (OCT) is an optical diagnostic modality that can acquire cross-sectional images of the microscopic structure of the esophagus, including Barrett's esophagus (BE) and associated dysplasia. We developed a swallowable tethered capsule OCT endomicroscopy (TCE) device that acquires high-resolution images of entire gastrointestinal (GI) tract luminal organs. This device has a potential to become a screening method that identifies patients with an abnormal esophagus that should be further referred for upper endoscopy. Currently, the characterization of the OCT-TCE esophageal wall data set is performed manually, which is time-consuming and inefficient. Additionally, since the capsule optics optimally focus light approximately 500 µm outside the capsule wall and the best quality images are obtained when the tissue is in full contact with the capsule, it is crucial to provide feedback for the operator about tissue contact during the imaging procedure. In this study, we developed a fully automated algorithm for the segmentation of in vivo OCT-TCE data sets and characterization of the esophageal wall. The algorithm provides a two-dimensional representation of both the contact map from the data collected in human clinical studies as well as a tissue map depicting areas of BE with or without dysplasia. Results suggest that these techniques can potentially improve the current TCE data acquisition procedure and provide an efficient characterization of the diseased esophageal wall. prospective trial comparing unsedated esophagoscopy via transnasal and transoral routes using a 4-mm video endoscope with conventional endoscopy with sedation," Endoscopy 37(6), 559-565 (2005).

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Depth-resolved model-based reconstruction of attenuation coefficients in optical coherence tomography

Cited by 297 publications

References 30 publications

Estimation of Jones matrix, birefringence and entropy using Cloude-Pottier decomposition in polarization-sensitive optical coherence tomography

Estimation of Jones matrix, birefringence and entropy using Cloude-Pottier decomposition in polarization-sensitive optical coherence tomography

Segmentation of thin corrugated layers in high-resolution OCT images

Automated segmentation and characterization of esophageal wall in vivo by tethered capsule optical coherence tomography endomicroscopy

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