Optical tomography system using charge-coupled device

This research presents an application of Charge-Coupled Device (CCD) linear sensor and laser diode in an optical tomography system. Optical tomography is a non-invasive and non-intrusive method of capturing a cross-sectional image of multiphase flow. The measurements are based on the final light intensity received by the sensor and this approach is limited to detecting solid objects only. The aim of this research was to analyse and demonstrate the capability of laser with a CCD in an optical tomography system for detecting different types of opaque objects in crystal clear water. The image reconstruction algorithms used in this research were filtered images of Linear Back Projection algorithms. These algorithms were programmed using LabVIEW programming software. Experiments in detecting solid and transparent objects were conducted, including experiments of rising air bubbles analysis. Based on the results, statistical analysis was performed to verify that the captured data were valid compared to the actual object data. The diameter and image of static solid and transparent objects were captured by this system, with 320 image views giving less area error than 160-views. This suggests that high image view resulted in high resolution image reconstruction. A moving object’s characteristics such as diameter, path and velocity can also be observed. The accuracy of this system in detecting object acceleration was 82%, while the average velocity of rising air bubbles captured was 0.2328 m/s. In conclusion, this research has successfully developed a non-intrusive and non-invasive optical tomography system that can detect static and moving objects in crystal clear water

Transfer of Individual Micro- and Nanoparticles for High- Precision 3D Analysis Using 360° Electron Tomography

A versatile approach is demonstrated, providing a general routine for an extensive and advanced 3D characterization of individually selected micro- and nanoparticles, enabling the combination of complementary and scale-bridging techniques. Quintessential to the method is the transfer of individual particles onto tailored tips using a conventional scanning electron microscope equipped with a suitable micromanipulator. The method enables a damage- and contamination-free preparation of freestanding particles. This is of significant importance for applications addressing the measurement of structural, physical, and chemical properties of specifically selected particles, such as 360° electron tomography, atom probe tomography, nano X-ray tomography, or optical near-field measurements. In this context, the method is demonstrated for 360° electron tomography of micro-/macroporous zeolite particles with sizes in the micrometer range and mesoporous alpha-hematite nanoparticles exhibiting sizes of 50–100 nm, including detailed pre- and postcharacterization on the nanoscale.“Deutsche Forschungsgemeinschaft” (DFG) within the framework of the SPP 1570 (project DFG SP 648/4-3 “3D analysis of complex pore structures using ET and high-resolution TEM”) and the research training group GRK 1896 (“In situ Microscopy with Electrons, X-rays and Scanning Probes”) as well as through the Cluster of Excellence “Engineering of Advanced Materials” at the Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany)FIBJulian Losche

Associations with photoreceptor thickness measures in the UK Biobank.

Spectral-domain OCT (SD-OCT) provides high resolution images enabling identification of individual retinal layers. We included 32,923 participants aged 40-69 years old from UK Biobank. Questionnaires, physical examination, and eye examination including SD-OCT imaging were performed. SD OCT measured photoreceptor layer thickness includes photoreceptor layer thickness: inner nuclear layer-retinal pigment epithelium (INL-RPE) and the specific sublayers of the photoreceptor: inner nuclear layer-external limiting membrane (INL-ELM); external limiting membrane-inner segment outer segment (ELM-ISOS); and inner segment outer segment-retinal pigment epithelium (ISOS-RPE). In multivariate regression models, the total average INL-RPE was observed to be thinner in older aged, females, Black ethnicity, smokers, participants with higher systolic blood pressure, more negative refractive error, lower IOPcc and lower corneal hysteresis. The overall INL-ELM, ELM-ISOS and ISOS-RPE thickness was significantly associated with sex and race. Total average of INL-ELM thickness was additionally associated with age and refractive error, while ELM-ISOS was additionally associated with age, smoking status, SBP and refractive error; and ISOS-RPE was additionally associated with smoking status, IOPcc and corneal hysteresis. Hence, we found novel associations of ethnicity, smoking, systolic blood pressure, refraction, IOPcc and corneal hysteresis with photoreceptor thickness

A Deep Learning Approach to Denoise Optical Coherence Tomography Images of the Optic Nerve Head

Purpose: To develop a deep learning approach to de-noise optical coherence tomography (OCT) B-scans of the optic nerve head (ONH). Methods: Volume scans consisting of 97 horizontal B-scans were acquired through the center of the ONH using a commercial OCT device (Spectralis) for both eyes of 20 subjects. For each eye, single-frame (without signal averaging), and multi-frame (75x signal averaging) volume scans were obtained. A custom deep learning network was then designed and trained with 2,328 "clean B-scans" (multi-frame B-scans), and their corresponding "noisy B-scans" (clean B-scans + gaussian noise) to de-noise the single-frame B-scans. The performance of the de-noising algorithm was assessed qualitatively, and quantitatively on 1,552 B-scans using the signal to noise ratio (SNR), contrast to noise ratio (CNR), and mean structural similarity index metrics (MSSIM). Results: The proposed algorithm successfully denoised unseen single-frame OCT B-scans. The denoised B-scans were qualitatively similar to their corresponding multi-frame B-scans, with enhanced visibility of the ONH tissues. The mean SNR increased from $4.02 \pm 0.68$ dB (single-frame) to $8.14 \pm 1.03$ dB (denoised). For all the ONH tissues, the mean CNR increased from $3.50 \pm 0.56$ (single-frame) to $7.63 \pm 1.81$ (denoised). The MSSIM increased from $0.13 \pm 0.02$ (single frame) to $0.65 \pm 0.03$ (denoised) when compared with the corresponding multi-frame B-scans. Conclusions: Our deep learning algorithm can denoise a single-frame OCT B-scan of the ONH in under 20 ms, thus offering a framework to obtain superior quality OCT B-scans with reduced scanning times and minimal patient discomfort

Agreement of Anterior Segment Parameters Obtained From Swept-Source Fourier-Domain and Time-Domain Anterior Segment Optical Coherence Tomography.

PurposeTo assess the interdevice agreement between swept-source Fourier-domain and time-domain anterior segment optical coherence tomography (AS-OCT).MethodsFifty-three eyes from 41 subjects underwent CASIA2 and Visante OCT imaging. One hundred eighty-degree axis images were measured with the built-in two-dimensional analysis software for the swept-source Fourier-domain AS-OCT (CASIA2) and a customized program for the time-domain AS-OCT (Visante OCT). In both devices, we examined the angle opening distance (AOD), trabecular iris space area (TISA), angle recess area (ARA), anterior chamber depth (ACD), anterior chamber width (ACW), and lens vault (LV). Bland-Altman plots and intraclass correlation (ICC) were performed. Orthogonal linear regression assessed any proportional bias.ResultsICC showed strong correlation for LV (0.925) and ACD (0.992) and moderate agreement for ACW (0.801). ICC suggested good agreement for all angle parameters (0.771-0.878) except temporal AOD500 (0.743) and ARA750 (nasal 0.481; temporal 0.481). There was a proportional bias in nasal ARA750 (slope 2.44, 95% confidence interval [CI]: 1.95-3.18), temporal ARA750 (slope 2.57, 95% CI: 2.04-3.40), and nasal TISA500 (slope 1.30, 95% CI: 1.12-1.54). Bland-Altman plots demonstrated in all measured parameters a minimal mean difference between the two devices (-0.089 to 0.063); however, evidence of constant bias was found in nasal AOD250, nasal AOD500, nasal AOD750, nasal ARA750, temporal AOD500, temporal AOD750, temporal ARA750, and ACD. Among the parameters with constant biases, CASIA2 tends to give the larger numbers.ConclusionsBoth devices had generally good agreement. However, there were proportional and constant biases in most angle parameters. Thus, it is not recommended that values be used interchangeably

The angular spectrum of the scattering coefficient map reveals subsurface colorectal cancer

Abstract Colorectal cancer diagnosis currently relies on histological detection of endoluminal neoplasia in biopsy specimens. However, clinical visual endoscopy provides no quantitative subsurface cancer information. In this ex vivo study of nine fresh human colon specimens, we report the first use of quantified subsurface scattering coefficient maps acquired by swept-source optical coherence tomography to reveal subsurface abnormities. We generate subsurface scattering coefficient maps with a novel wavelet-based-curve-fitting method that provides significantly improved accuracy. The angular spectra of scattering coefficient maps of normal tissues exhibit a spatial feature distinct from those of abnormal tissues. An angular spectrum index to quantify the differences between the normal and abnormal tissues is derived, and its strength in revealing subsurface cancer in ex vivo samples is statistically analyzed. The study demonstrates that the angular spectrum of the scattering coefficient map can effectively reveal subsurface colorectal cancer and potentially provide a fast and more accurate diagnosis

OCT for glaucoma diagnosis, screening and detection of glaucoma progression.

Optical coherence tomography (OCT) is a commonly used imaging modality in the evaluation of glaucomatous damage. The commercially available spectral domain (SD)-OCT offers benefits in glaucoma assessment over the earlier generation of time domain-OCT due to increased axial resolution, faster scanning speeds and has been reported to have improved reproducibility but similar diagnostic accuracy. The capabilities of SD-OCT are rapidly advancing with 3D imaging, reproducible registration, and advanced segmentation algorithms of macular and optic nerve head regions. A review of the evidence to date suggests that retinal nerve fibre layer remains the dominant parameter for glaucoma diagnosis and detection of progression while initial studies of macular and optic nerve head parameters have shown promising results. SD-OCT still currently lacks the diagnostic performance for glaucoma screening